The group said most people have adequate amounts of vitamin D in their blood supplied by their diets and natural sources like sunshine, the committee says in a report that is to be released on Tuesday.

“For most people, taking extra calcium and vitamin D supplements is not indicated,” said Dr. Clifford J. Rosen, a member of the panel and an osteoporosis expert at the Maine Medical Center Research Institute.

Dr. J. Christopher Gallagher, director of the bone metabolism unit at the Creighton University School of Medicine in Omaha, Neb., agreed, adding, “The onus is on the people who propose extra calcium and vitamin D to show it is safe before they push it on people.”

Over the past few years, the idea that nearly everyone needs extra calcium and vitamin D — especially vitamin D — has swept the nation.

With calcium, adolescent girls may be the only group that is getting too little, the panel found. Older women, on the other hand, may take too much, putting themselves at risk for kidney stones. And there is evidence that excess calcium can increase the risk of heart disease, the group wrote.

As for vitamin D, some prominent doctors have said that most people need supplements or they will be at increased risk for a wide variety of illnesses, including heart disease, cancer and autoimmune diseases.

And these days more and more people know their vitamin D levels because they are being tested for it as part of routine physical exams.

“The number of vitamin D tests has exploded,” said Dennis Black, a reviewer of the report who is a professor of epidemiology and biostatistics at the University of California, San Francisco.

At the same time, vitamin D sales have soared, growing faster than those of any supplement, according to The Nutrition Business Journal. Sales rose 82 percent from 2008 to 2009, reaching $430 million. “Everyone was hoping vitamin D would be kind of a panacea,” Dr. Black said. The report, he added, might quell the craze.

“I think this will have an impact on a lot of primary care providers,” he said.

The 14-member expert committee was convened by the Institute of Medicine, an independent nonprofit scientific body, at the request of the United States and Canadian governments. It was asked to examine the available data — nearly 1,000 publications — to determine how much vitamin D and calcium people were getting, how much was needed for optimal health and how much was too much.

The two nutrients work together for bone health.

Bone health, though, is only one of the benefits that have been attributed to vitamin D, and there is not enough good evidence to support most other claims, the committee said.

Some labs have started reporting levels of less than 30 nanograms of vitamin D per milliliter of blood as a deficiency. With that as a standard, 80 percent of the population would be deemed deficient of vitamin D, Dr. Rosen said. Most people need to take supplements to reach levels above 30 nanograms per milliliter, he added.

But, the committee concluded, a level of 20 to 30 nanograms is all that is needed for bone health, and nearly everyone is in that range.

Vitamin D is being added to more and more foods, said Paul R. Thomas of the Office of Dietary Supplements at the National Institutes of Health. Not only is it in orange juice and milk, but more is being added to breakfast cereals, and it now can be found in very high doses in supplement pills. Most vitamin D pills, he said, used to contain no more than 1,000 international units of it. Now it is easy to find pills, even in places like Wal-Mart, with 5,000 international units. The committee, though, said people need only 600 international units a day.

To assess the amounts of vitamin D and calcium people are getting, the panel looked at national data on diets. Most people, they concluded, get enough calcium from the foods they eat, about 1,000 milligrams a day for most adults (1,200 for women ages 51 to 70).

Vitamin D is more complicated, the group said. In general, most people are not getting enough vitamin D from their diets, but they have enough of the vitamin in their blood, probably because they are also making it naturally after being out in the sun and storing it in their bodies.

The American Society for Bone and Mineral Research and other groups applauded the report. It is “a very balanced set of recommendations,” said Dr. Sundeep Khosla, a Mayo Clinic endocrinologist and the society’s president.

But Andrew Shao, an executive vice president at the Council for Responsible Nutrition, a trade group, said the panel was being overly cautious, especially in its recommendations about vitamin D. He said there was no convincing evidence that people were being harmed by taking supplements, and he said higher levels of vitamin D, in particular, could be beneficial.

Such claims “are not supported by the available evidence,” the committee wrote. They were based on studies that observed populations and concluded that people with lower levels of the vitamin had more of various diseases. Such studies have been misleading and most scientists agree that they cannot determine cause and effect.

It is not clear how or why the claims for high vitamin D levels started, medical experts say. First there were two studies, which turned out to be incorrect, that said people needed 30 nanograms of vitamin D per milliliter of blood, the upper end of what the committee says is a normal range. They were followed by articles and claims and books saying much higher levels — 40 to 50 nanograms or even higher — were needed.

After reviewing the data, the committee concluded that the evidence for the benefits of high levels of vitamin D was “inconsistent and/or conflicting and did not demonstrate causality.”

Evidence also suggests that high levels of vitamin D can increase the risks for fractures and the overall death rate and can raise the risk for other diseases. While those studies are not conclusive, any risk looms large when there is no demonstrable benefit. Those hints of risk are “challenging the concept that ‘more is better,’ ” the committee wrote.

That is what surprised Dr. Black. “We thought that probably higher is better,” he said.

He has changed his mind, and expects others will too: “I think this report will make people more cautious.”

Martinez F, Kamar N, Pallet N, Lang P, Durrbach A, Lebranchu Y, Adem A, Barbier S, Cassuto-Viguier E, Glowaki F, Le Meur Y, Rostaing L, Legendre C, Hermine O, Choukroun G; NeoPDGF Study Investigators. Am J Transplant. 2010 Jul;10(7):1695-700.

Erythropoietin promotes nephroprotection in animal models of ischemia-reperfusion injury. Neorecormon and Prevention of Delayed Graft Function (Neo-PDGF) is a French open-label multicenter randomized study to evaluate the effect of high doses of epoetin beta (EPO-beta) during the first 2 weeks of renal transplantation on renal function in patients at risk for delayed graft function (DGF). One hundred and four patients were included in the study. Patients randomized in treatment group (A) received four injections of EPO-beta (30.000 UI each), given before surgery and at 12 h, 7 days and 14 days posttransplantation. Patients randomized in control group (B) did not receive EPO-beta. Immunosuppression included induction with basiliximab and maintenance therapy with steroids, mycophenolate mofetil and tacrolimus. At 1 month posttransplant, the estimated glomerular filtration rate (MDRD formula) was 42.5 +/- 19.0 mL/min in the EPO-beta group and 44.0 +/- 16.3 mL/min in the control group (p = ns). The frequency of DGF was similar in both groups (32% vs. 38.8%; p = ns). No difference in the incidence of serious adverse events was observed. (ClinicalTrials.gov number, NCT00815867.).

*The CLEAR study: a 5-day, 3-g loading dose of mycophenolate mofetil versus standard 2-g dosing in renal transplantation.*

Gourishankar S, Houde I, Keown PA, Landsberg D, Cardella CJ, Barama AA, Dandavino R, Shoker A, Pirc L, Wrobel MM, Kiberd BA. Clin J Am Soc Nephrol. 2010 Jul;5(7):1282-9. Epub 2010 May 24.

BACKGROUND AND OBJECTIVES: Adequate early mycophenolic acid (MPA) exposure is associated with lower rates of acute rejection in renal transplantation. The aim of this randomized controlled trial was to determine if higher initial mycophenolate mofetil (MMF) doses increased the proportion of patients reaching therapeutic MPA levels (30 to 60 mg.h/L) by day 5. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: De novo renal transplant patients were randomized to receive intensified dosing of MMF (1.5 g twice daily on days 1 to 5, then 1.0 g twice daily) or standard dosing (1.0 g twice daily). All recipients received tacrolimus and prednisone. Full MPA areas under the curve (AUCs) were completed on days 3 and 5, whereas a limited sampling strategy was utilized at four subsequent time points. RESULTS: At day 5, 47.5% of the MMF 3-g arm achieved the MPA therapeutic window versus 54.4% of the MMF 2-g arm. However, MPA AUC levels were significantly higher in the 3-g arm at day 3 and 5. This resulted in a trend for fewer treated acute rejections at 6 months. Significantly more acute rejections (treated, biopsy-proven including and excluding borderline) occurred in patients with MPA AUC levels<30 mg.h/L compared with those >or=30 mg.h/L at day 5. No significant differences were seen in common adverse events. CONCLUSIONS: A limited intensified dose of MMF increased early MPA exposure and was well tolerated. Further studies are required to determine whether limited intensified MMF dosing can reduce acute rejection.

*Mycophenolic acid exposure in high- and low-weight renal transplant patients after dosing with mycophenolate mofetil in the Opticept trial.*

Kaplan B, Gaston RS, Meier-Kriesche HU, Bloom RD, Shaw LM. Ther Drug Monit. 2010 Apr;32(2):224-7.

The Opticept trial was an open-label, randomized, multicenter trial involving 720 kidney recipients. Three immunosuppressant dosing regimens were evaluated, including both fixed and concentration-controlled dosing of mycophenolate mofetil in combination with standard and reduced calcineurin inhibitor levels. Mycophenolic acid (MPA) levels were measured, yielding one of the largest databases to assess the impact of variables on MPA exposure. The present subset analysis evaluated the effect of baseline body weight in three noncontiguous weight categories on MPA exposure at steady state (Day 90) in patients receiving tacrolimus. Multivariate linear regression models assessed the relationship between area under the concentration-time curve (AUC) and several variables. In all, 219 patients had baseline weights in the three categories and an MPA AUC at Day 90: 50 kg or less (n = 12, all female); 60 to 80 kg (n = 136); or 100 kg or greater (n = 71). In overall comparisons by weight class, clearance increased with increased weight, resulting in an inverse relationship between dose-corrected MPA AUCs and weight at Day 90 (P < 0.0001). In patients of extreme weight, wide disparities of MPA exposure were measured despite the mean mycophenolate mofetil dose, notably in those 50 kg or less who had comparatively high dose-corrected MPA AUCs. Patients at the extremes of weight might be at risk of over- or underimmunosuppression unless doses are adjusted.

BACKGROUND: The high mortality rate among critically ill patients with acute kidney injury (AKI) remains an unsolved problem in intensive care medicine, despite the use of renal replacement therapy (RRT). Increasing evidence from clinical studies in adults and children suggests that the new peritoneal dialysis (PD) fluids may allow for better long-term preservation of peritoneal morphology and function. Formation of glucose degradation products (GDPs) can be reduced and even avoided with the use of newer “biocompatible” solutions. However, it is still unclear if there are any differences in using conventional (lactate) solutions compared with low GDP (bicarbonate) solutions for acute PD. OBJECTIVES: To look at the benefits and harms of bicarbonate versus lactate solutions in acute PD. SEARCH STRATEGY: We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (from 1966), EMBASE (from 1980), Latin American and Caribbean Health Sciences Literature Database LILACS (from 1982), and reference lists of articles. SELECTION CRITERIA: Randomised controlled trials (RCTs) comparing bicarbonate to lactate solution for acute PD. DATA COLLECTION AND ANALYSIS: Two authors independently assess the methodological quality of studies. One author abstracted data onto a standard form, and a second author checked data extraction. We used the random-effects model and expressed the results as relative risk (RR) for dichotomous outcomes and mean difference (MD) for continuous outcomes with 95% confidence intervals (CI). MAIN RESULTS: We included one study (20 patients) in this review. In shock patients, bicarbonate did not differ from lactate with respect to mortality (RR 0.50, 95% CI 0.06 to 3.91); however there were significant differences in blood lactate (MD -1.60 mmol/L, 95% CI -2.04 to -1.16), serum bicarbonate (MD 5.00 mmol/L, 95% CI 3.26 to 6.74) and blood pH (MD 0.12, 95% CI 0.06 to 0.18). In non-shock patients there was a significance difference in blood lactate (MD -0.60 mmol/L, 95% CI -0.85 to -0.35) but not in serum bicarbonate (MD 1.10 mmol/L, 95% CI -0.27 to 2.47) or blood pH (MD -0.02, 95% CI -0.02 to -0.06). Other outcomes could not be analysed because of the limited data available. AUTHORS’ CONCLUSIONS: There is no strong evidence that any clinical advantage for patients requiring acute PD for AKI when comparing conventional (lactate) with low GDP dialysis solutions (bicarbonate).

*Defining acute kidney injury in database studies: the effects of varying the baseline kidney function assessment period and considering CKD status.*

Lafrance JP, Miller DR. Am J Kidney Dis. 2010 Oct;56(4):651-60. Epub 2010 Jul 29.

BACKGROUND: Existing acute kidney injury (AKI) definitions are not well adapted for database studies, leading to a great variety of methods used in research. Variations in time before hospitalization used to assess baseline kidney function when identifying episodes of AKI may lead to different case samples and mortality risks in database studies, but the magnitude of these effects is not known. STUDY DESIGN: A retrospective cohort study. SETTINGS & PARTICIPANTS: 1,126,636 veterans hospitalized at least once within the US Department of Veterans Affairs health care system between 2000 and 2005. PREDICTOR: AKI was defined by comparing (using ratio [?1.5] or difference [increase of 0.3-0.5 mg/dL]) the highest serum creatinine level during hospitalization with the lowest level during 4 different baseline assessment periods (in-hospital only and 3, 6, or 12 months preadmission). OUTCOMES & MEASUREMENTS: In-hospital mortality risk was estimated using multivariable logistic regression models. RESULTS: Using the ratio definition, the cumulative incidence of AKI ranged from 12.5% (in-hospital only) to 18.3% (12 months preadmission). Newly added cases had milder AKI and lower mortality risk. The discriminative power increased slightly (C statistic increased from 0.846 to 0.855; P = 0.001) by extending the baseline period to at least 3 months. Both the ratio and difference definitions did not perform well in patients with chronic kidney disease stages 4 and 5. LIMITATIONS: Possibility of residual confounding and under-representation of women (4.5%). CONCLUSIONS: Many additional AKI cases may be identified by extending the baseline assessment period; however, added cases may be less severe with lower mortality risk. The relative strengths of these biases and combined effects of reducing misclassification (identification of more AKI cases) and increasing risk dilution (identifying milder cases) may vary across populations. Consensus regarding how baseline kidney function should be determined in database studies should be reached.

*Impact of RIFLE classification in liver transplantation.*

Ferreira AC, Nolasco F, Carvalho D, Sampaio S, Baptista A, Pessegueiro P, Monteiro E, Mourão L, Barroso E. Clin Transplant. 2010 May;24(3):394-400. Epub 2009 Sep 11.

Acute renal failure (ARF) is common after orthotopic liver transplantation (OLT). The aim of this study was to evaluate the prognostic value of RIFLE classification in the development of CKD, hemodialysis requirement, and mortality. Patients were categorized as risk (R), injury (I) or failure (F) according to renal function at day 1, 7 and 21. Final renal function was classified according to K/DIGO guidelines. We studied 708 OLT recipients, transplanted between September 1992 and March 2007; mean age 44 +/- 12.6 yr, mean follow-up 3.6 yr (28.8% > or = 5 yr). Renal dysfunction before OLT was known in 21.6%. According to the RIFLE classification, ARF occurred in 33.2%: 16.8% were R class, 8.5% I class and 7.9% F class. CKD developed in 45.6%, with stages 4 or 5d in 11.3%. Mortality for R, I and F classes were, respectively, 10.9%, 13.3% and 39.3%. Severity of ARF correlated with development of CKD: stage 3 was associated with all classes of ARF, stages 4 and 5d only with severe ARF. Hemodialysis requirement (23%) and mortality were only correlated with the most severe form of ARF (F class). In conclusion, RIFLE classification is a useful tool to stratify the severity of early ARF providing a prognostic indicator for the risk of CKD occurrence and death.

*Urinary L-type fatty acid-binding protein as a new biomarker of sepsis complicated with acute kidney injury. *Doi K, Noiri E, Maeda-Mamiya R, Ishii T, Negishi K, Hamasaki Y, Fujita T, Yahagi N, Koide H, Sugaya T, Nakamura T. Crit Care Med. 2010 Oct;38(10):2037-42.

OBJECTIVE: This study is aimed to examine whether urinary L-type fatty acid-binding protein can detect the severity of sepsis with animal sepsis models and septic shock patients complicated with established acute kidney injury. DESIGN: Experimental animal models and a clinical, prospective observational study. SETTING: University laboratory and tertiary hospital. SUBJECTS AND PATIENTS: One hundred fourteen human L-type fatty acid-binding protein transgenic mice and 145 septic shock patients with established acute kidney injury. INTERVENTIONS: Animals were challenged by abdominal (cecal ligation and puncture) and pulmonary (intratracheal lipopolysaccharide injection) sepsis models with different severities that were confirmed by survival analysis (n = 24) and bronchoalveolar lavage fluid analysis (n = 38). MEASUREMENTS AND MAIN RESULTS: In animal experiments, significant increases of urinary L-type fatty acid-binding protein levels were induced by sepsis (severe cecal ligation and puncture 399.0 ± 226.8 ?g/g creatinine [n = 12], less-severe cecal ligation and puncture 89.1 ± 25.3 [n = 11], sham 13.4 ± 3.4 [n = 10] at 6 hrs, p < .05 vs. sham; 200 ?g of lipopolysaccharide 190.6 ± 77.4 ?g/g creatinine [n = 6], 50 ?g of lipopolysaccharide 145.4 ± 32.6 [n = 8], and saline 29.9 ± 14.9 [n = 5] at 6 hrs, p < .05 vs. saline). Urinary L-type fatty acid-binding protein predicted severity more accurately than blood urea nitrogen, serum creatinine, and urinary N-acetyl-d-glucosaminidase levels. In clinical evaluation, urinary L-type fatty acid-binding protein measured at admission was significantly higher in the nonsurvivors of septic shock with established acute kidney injury than in the survivors (4366 ± 192 ?g/g creatinine [n = 68] vs. 483 ± 71 [n = 77], p < .05). Urinary L-type fatty acid-binding protein showed the higher value of area under the receiver operating characteristic curve for mortality compared with Acute Physiology and Chronic Health Evaluation (APACHE) II and Sepsis-related Organ Failure Assessment (SOFA) scores (L-type fatty acid-binding protein 0.994 [0.956-0.999], APACHE II 0.927 [0.873-0.959], and SOFA 0.813 [0.733-0.873], p < .05). CONCLUSIONS: Our results suggest that urinary L-type fatty acid-binding protein can be a useful biomarker for sepsis complicated with acute kidney injury for detecting its severity.

By TINA ROSENBERG AND DAVID BORNSTEIN

Most of us tend to be better informed about problems than solutions. This presents two challenges: if we rarely hear about success when it occurs, it’s hard to believe that problems can, in fact, be solved. Also, knowledge about how to solve problems ends up being concentrated in too few hands. It needs to circulate more broadly so that it can be applied where needed.

Today, we will examine one solution to a vexing problem: many diseases that we know how to prevent and cure remain widespread. For nearly all of human history, lives were short and miserable because there was little anyone could do about disease. Now we know what to do. The science is there. The technology is there. But we have a different problem ? a happier one, but no less challenging: how do we get these interventions to people everywhere? And this problem doesn’t just apply to health care, it applies to almost every modern good or service, whether it’s education, energy, clean water or job opportunities. As the science fiction writer William Gibson has said, “The future is here ? it’s just not evenly distributed.”

That’s why we’re beginning with the story of a health assistant named Tsepo Kotelo, whose job is to take care of people in remote mountain villages in the Maseru district of Lesotho. Kotelo’s story shows the critical need for something not usually on the global to-do list for Third World health: motorcycle maintenance.

Lesotho has some of the world’s highest rates of AIDS and tuberculosis, and much of Kotelo’s time is spent counseling and testing people for these diseases, giving talks about AIDS prevention, and helping people stick to their treatment plans and deal with side effects. He also checks the water supply, helps villagers improve sanitation, weighs and immunizes babies, examines pregnant women and treats basic diseases.

Until 2008 Kotelo could visit only three villages a week, because he had to reach them on foot, walking for miles and miles. But in February of that year, Kotelo got a motorcycle ? the best vehicle for reaching rural villages in Africa, most of which are nowhere near a real road. Just as crucial, he was given the tools to keep the bike on the road: he received a helmet and protective clothing, he was taught to ride and trained to start each day with a quick check of the bike. His motorcycle is also tuned up monthly by a technician who comes to him. Now, instead of spending his days walking to his job, he can do his job. Instead of visiting three villages each week, he visits 20. Where else can you find a low-tech investment in health care that increases patient coverage by nearly 600 percent? Tom Oldham/Riders for Health. A peer mentor for H.I.V.-positive pregnant women and new mothers travels through Lesotho on a motorcycle maintained by Riders for Health..

Kotelo’s four colleagues also received motorcycles, and now every village in the Maseru district has health care. The area also now has five motorcycle couriers who drive blood or sputum samples from villages to local laboratories ? particularly important to test for H.I.V. and TB, and to see if the medicines are working. The couriers get the same training and gear as Kotelo, plus special temperature-controlled, vibration-smoothing backpacks. Before, samples were packed in plastic bags and walked to clinics. They would usually arrive late, boiled or shaken beyond use ? if they got there at all.

The motorcycles come from the Elton John AIDS Foundation, but the maintenance comes from Riders for Health, a British-based organization founded by a husband and wife team, Barry and Andrea Coleman. The idea began in 1988, during a visit by the American motorcycle racing star Randy Mamola to Somalia. Mamola had given a sizeable donation to Save the Children, and had been invited to see its work in person. He asked Andrea Coleman, who did public relations work for him and helped him raise money for charity, to come along. She had young children and declined, but suggested Mamola take her husband, Barry, who wrote about motorcycle racing for The Guardian newspaper.

It was the first of several trips for Mamola and the Colemans. In Somalia, they saw a woman in distressed labor being pushed towards the health clinic in a wheelbarrow. They visited villages and heard that no one had ever come to vaccinate children. Yet they also saw a graveyard of dead motorcycles and ambulances behind the clinic, some of them discarded for want of a $3 part and a little know-how. “Some of them were relatively new,” said Andrea Coleman. “This was crazy. It’s been 100 years since the internal combustion engine was invented and nobody knew how to deal with these vehicles. What a waste of money and lives.” Today the Colemans run Riders.

There’s nothing new about donating vehicles for health care in Africa. Many organizations do it. But often these vehicles fall apart. Barry Coleman says that unmanaged, a vehicle in Africa will usually have a major breakdown after 8 months of use and be junked entirely by 15 months. This is a classic problem in development: everybody wants to play the white knight coming to the rescue with the quick fix — the water pump, the $100 laptop, the motorcycle. But the tougher challenge is developing a cost-effective system to keep things working.

In some countries, Riders provides vehicles ? for example Gambia’s health system leases all its vehicles from Riders. But what makes Riders different is that in all of the seven countries it works in, it focuses on keeping the vehicles running. Riders charges a fixed cost of about 18 cents per kilometer for motorcycles, which includes fuel, and keeps vehicles in constant use for years with no breakdowns. It trains and hires local technicians to do monthly tune-ups. The predictable fees help governments and aid groups incorporate maintenance in their budget planning. Riders currently manages about 1,200 motorcycles, ambulances and four-wheel drive vehicles used for health care in Africa. The vast majority are motorcycles ? even some ambulances are motorcycles with sidecars.

We’re not suggesting that motorcycles will solve Africa’s health problems ? not even its health delivery problems. The continent is facing a severe shortage of health care workers. (Thousands are poached each year by wealthy countries; we’ll write about some fixes for this in future columns.) But it’s within easy reach to multiply the scope and efficiency of the people who are already on the ground.

We already mentioned that Tsepo Kotelo’s motorcycle allows him to serve almost seven times as many villages as before. Kotelo can also respond to emergencies, so he can provide better care as well as more of it. And visiting villages more frequently, he can catch illnesses in their early stages or prevent them entirely. A woman with a breach baby can make it to the hospital in time — by sidecar ambulance, no wheelbarrow necessary. People now give sputum samples for TB diagnoses because they trust that their samples will actually reach the laboratory unspoiled. All these changes save lives.

Dependable transport could revolutionize more than health care. In poor countries, rural schools often lack teachers, who don’t want to live in villages. If they could commute to work by motorcycle, more village children would be educated. Additionally, water and electrification projects remain stalled across Africa because district government offices don’t even have one bike to make site visits.

Riders dramatizes the importance of paying attention to the scruffy and mundane parts of a system, especially delivery. Businesses understand this. If Federal Express didn’t maintain its trucks, it would go bankrupt. The same applies to social interventions. It doesn’t matter how many billions have been spent on life-saving drugs or how well-trained the nurses are if a clogged fuel line prevents the treatments from reaching the patient.

Riders for Health’s focus on motorcycle maintenance is an example of the creative and practical ideas we look forward to debating with interested readers as this column develops. We hope these ideas will also lead to discussions of the big questions about social change.

David Bornstein is the author of “How to Change the World,” which has been published in 20 languages, and “The Price of a Dream: The Story of the Grameen Bank,” and is co-author of “Social Entrepreneurship: What Everyone Needs to Know.” He is the founder of dowser.org, a media site that reports on social innovation.

Tina Rosenberg won a Pulitzer Prize for her book “The Haunted Land: Facing Europe’s Ghosts After Communism.” She is a former editorial writer for The Times and now a contributing writer for the paper’s Sunday magazine. Her new book, “Join the Club: How Peer Pressure Can Transform the World,” is forthcoming from W.W. Norton.

The American Heart Association has created a short web tutorial that shows how to do effective CPR. It’s available at handsonlycpr.org/.  Forget about yucky mouth-to-mouth contact — the P in cardiopulmonary resuscitation (CPR) — and get right down to pumping hard and fast on the chest, the American Heart Association said on Monday, that will keep oxygen-rich blood flowing to the brain until trained rescuers can take over.

“Chest compressions are the most important part of CPR,” said Dr. Michael Sayre, a spokesman for the American Heart Association. “The major change is switching to starting CPR with chest compressions rather than opening an airway and doing rescue breathing.”

Only if a rescuer has been specifically trained in conventional CPR should they give rescue breathing as well, added Sayre, also of Ohio State University in Columbus.

Recent studies have shown that CPR without rescue breathing works as well as or better than the full version in most people who suffer cardiac arrest.

And it might also get more people to do CPR, which is currently performed only about half the time when someone witnesses a person collapse from cardiac arrest. Some 300,000 Americans suffer cardiac arrests every year, and less than one in 10 survive.

That dismal number hasn’t changed in three decades. But doctors say it could, and part of the solution is to get more bystanders to roll up their sleeves and start chest compressions in the center of the chest.

The ideal rate is at least 100 compressions per minute — coincidentally, about the same pace as the Bee Gees 1977 disco hit “Stayin’ Alive.” Each compression should be about two inches (five centimeters) deep in adults and children, and about one and a half inches in infants. Rescuers should not lean on the chest between compressions; it’s important to let the chest return to its starting position.

“If you see the victim suddenly collapse — one minute they’re walking and talking and the next minute they are on the ground — then the odds are high that it is cardiac arrest,” Sayre said.

If the victim is not breathing or not breathing normally, “Tap on their shoulder to see if you can wake them up. If you can’t, then we recommend starting chest compressions after calling 911.”

If you start CPR on someone who collapsed for some reason other than a cardiac arrest, “they usually just wake up,” said Sayre, adding that serious injuries were rare.

Earlier this month, Arizona saw the effects of a state-wide campaign to get bystanders to do hands-only CPR.

Five years after health officials started promoting the technique, the chances of surviving a cardiac arrest had more than doubled, reaching close to 10 percent. And those victims who received hands-only CPR had more than 1.5 times the odds of making it compared to those who got conventional CPR (see Reuters Health story of Oct 5, 2010).

“I don’t see any reason why in the future you wouldn’t have a better chance of surviving than dying of a cardiac arrest,” Dr. Bentley J. Bobrow, of Arizona’s Bureau of Emergency Medical Services & Trauma System, told Reuters Health at the time.

He noted, however, that factors such as public-access defibrillators

IN 2001, RUMORS were circulating in Greek hospitals that surgery residents, eager to rack up scalpel time, were falsely diagnosing hapless Albanian immigrants with appendicitis. At the University of Ioannina medical school’s teaching hospital, a newly minted doctor named Athina Tatsioni was discussing the rumors with colleagues when a professor who had overheard asked her if she’d like to try to prove whether they were true—he seemed to be almost daring her. She accepted the challenge and, with the professor’s and other colleagues’ help, eventually produced a formal study showing that, for whatever reason, the appendices removed from patients with Albanian names in six Greek hospitals were more than three times as likely to be perfectly healthy as those removed from patients with Greek names. “It was hard to find a journal willing to publish it, but we did,” recalls Tatsioni.. “I also discovered that I really liked research.” Good thing, because the study had actually been a sort of audition. The professor, it turned out, had been putting together a team of exceptionally brash and curious young clinicians and Ph.D.s to join him in tackling an unusual and controversial agenda.

Last spring, I sat in on one of the team’s weekly meetings on the medical school’s campus, which is plunked crazily across a series of sharp hills. The building in which we met, like most at the school, had the look of a barracks and was festooned with political graffiti. But the group convened in a spacious conference room that would have been at home at a Silicon Valley start-up. Sprawled around a large table were Tatsioni and eight other youngish Greek researchers and physicians who, in contrast to the pasty younger staff frequently seen in U.S. hospitals, looked like the casually glamorous cast of a television medical drama. The professor, a dapper and soft-spoken man named John Ioannidis, loosely presided.

One of the researchers, a biostatistician named Georgia Salanti, fired up a laptop and projector and started to take the group through a study she and a few colleagues were completing that asked this question: were drug companies manipulating published research to make their drugs look good? Salanti ticked off data that seemed to indicate they were, but the other team members almost immediately started interrupting. One noted that Salanti’s study didn’t address the fact that drug-company research wasn’t measuring critically important “hard” outcomes for patients, such as survival versus death, and instead tended to measure “softer” outcomes, such as self-reported symptoms (“my chest doesn’t hurt as much today”). Another pointed out that Salanti’s study ignored the fact that when drug-company data seemed to show patients’ health improving, the data often failed to show that the drug was responsible, or that the improvement was more than marginal.

Salanti remained poised, as if the grilling were par for the course, and gamely acknowledged that the suggestions were all good—but a single study can’t prove everything, she said. Just as I was getting the sense that the data in drug studies were endlessly malleable, Ioannidis, who had mostly been listening, delivered what felt like a coup de grâce: wasn’t it possible, he asked, that drug companies were carefully selecting the topics of their studies—for example, comparing their new drugs against those already known to be inferior to others on the market—so that they were ahead of the game even before the data juggling began? “Maybe sometimes it’s the questions that are biased, not the answers,” he said, flashing a friendly smile. Everyone nodded. Though the results of drug studies often make newspaper headlines, you have to wonder whether they prove anything at all. Indeed, given the breadth of the potential problems raised at the meeting, can any medical-research studies be trusted?

That question has been central to Ioannidis’s career. He’s what’s known as a meta-researcher, and he’s become one of the world’s foremost experts on the credibility of medical research. He and his team have shown, again and again, and in many different ways, that much of what biomedical researchers conclude in published studies—conclusions that doctors keep in mind when they prescribe antibiotics or blood-pressure medication, or when they advise us to consume more fiber or less meat, or when they recommend surgery for heart disease or back pain—is misleading, exaggerated, and often flat-out wrong. He charges that as much as 90 percent of the published medical information that doctors rely on is flawed. His work has been widely accepted by the medical community; it has been published in the field’s top journals, where it is heavily cited; and he is a big draw at conferences. Given this exposure, and the fact that his work broadly targets everyone else’s work in medicine, as well as everything that physicians do and all the health advice we get, Ioannidis may be one of the most influential scientists alive. Yet for all his influence, he worries that the field of medical research is so pervasively flawed, and so riddled with conflicts of interest, that it might be chronically resistant to change—or even to publicly admitting that there’s a problem.

THE CITY OF IOANNINA is a big college town a short drive from the ruins of a 20,000-seat amphitheater and a Zeusian sanctuary built at the site of the Dodona oracle. The oracle was said to have issued pronouncements to priests through the rustling of a sacred oak tree. Today, a different oak tree at the site provides visitors with a chance to try their own hands at extracting a prophecy. “I take all the researchers who visit me here, and almost every single one of them asks the tree the same question,” Ioannidis tells me, as we contemplate the tree the day after the team’s meeting. “‘Will my research grant be approved?’” He chuckles, but Ioannidis (pronounced yo-NEE-dees) tends to laugh not so much in mirth as to soften the sting of his attack. And sure enough, he goes on to suggest that an obsession with winning funding has gone a long way toward weakening the reliability of medical research.

He first stumbled on the sorts of problems plaguing the field, he explains, as a young physician-researcher in the early 1990s at Harvard. At the time, he was interested in diagnosing rare diseases, for which a lack of case data can leave doctors with little to go on other than intuition and rules of thumb. But he noticed that doctors seemed to proceed in much the same manner even when it came to cancer, heart disease, and other common ailments. Where were the hard data that would back up their treatment decisions? There was plenty of published research, but much of it was remarkably unscientific, based largely on observations of a small number of cases. A new “evidence-based medicine” movement was just starting to gather force, and Ioannidis decided to throw himself into it, working first with prominent researchers at Tufts University and then taking positions at Johns Hopkins University and the National Institutes of Health. He was unusually well armed: he had been a math prodigy of near-celebrity status in high school in Greece, and had followed his parents, who were both physician-researchers, into medicine. Now he’d have a chance to combine math and medicine by applying rigorous statistical analysis to what seemed a surprisingly sloppy field. “I assumed that everything we physicians did was basically right, but now I was going to help verify it,” he says. “All we’d have to do was systematically review the evidence, trust what it told us, and then everything would be perfect.”

It didn’t turn out that way. In poring over medical journals, he was struck by how many findings of all types were refuted by later findings. Of course, medical-science “never minds” are hardly secret. And they sometimes make headlines, as when in recent years large studies or growing consensuses of researchers concluded that mammograms, colonoscopies, and PSA tests are far less useful cancer-detection tools than we had been told; or when widely prescribed antidepressants such as Prozac, Zoloft, and Paxil were revealed to be no more effective than a placebo for most cases of depression; or when we learned that staying out of the sun entirely can actually increase cancer risks; or when we were told that the advice to drink lots of water during intense exercise was potentially fatal; or when, last April, we were informed that taking fish oil, exercising, and doing puzzles doesn’t really help fend off Alzheimer’s disease, as long claimed. Peer-reviewed studies have come to opposite conclusions on whether using cell phones can cause brain cancer, whether sleeping more than eight hours a night is healthful or dangerous, whether taking aspirin every day is more likely to save your life or cut it short, and whether routine angioplasty works better than pills to unclog heart arteries.

But beyond the headlines, Ioannidis was shocked at the range and reach of the reversals he was seeing in everyday medical research. “Randomized controlled trials,” which compare how one group responds to a treatment against how an identical group fares without the treatment, had long been considered nearly unshakable evidence, but they, too, ended up being wrong some of the time. “I realized even our gold-standard research had a lot of problems,” he says. Baffled, he started looking for the specific ways in which studies were going wrong. And before long he discovered that the range of errors being committed was astonishing: from what questions researchers posed, to how they set up the studies, to which patients they recruited for the studies, to which measurements they took, to how they analyzed the data, to how they presented their results, to how particular studies came to be published in medical journals.

This array suggested a bigger, underlying dysfunction, and Ioannidis thought he knew what it was. “The studies were biased,” he says. “Sometimes they were overtly biased. Sometimes it was difficult to see the bias, but it was there.” Researchers headed into their studies wanting certain results—and, lo and behold, they were getting them. We think of the scientific process as being objective, rigorous, and even ruthless in separating out what is true from what we merely wish to be true, but in fact it’s easy to manipulate results, even unintentionally or unconsciously. “At every step in the process, there is room to distort results, a way to make a stronger claim or to select what is going to be concluded,” says Ioannidis. “There is an intellectual conflict of interest that pressures researchers to find whatever it is that is most likely to get them funded.”

Perhaps only a minority of researchers were succumbing to this bias, but their distorted findings were having an outsize effect on published research. To get funding and tenured positions, and often merely to stay afloat, researchers have to get their work published in well-regarded journals, where rejection rates can climb above 90 percent. Not surprisingly, the studies that tend to make the grade are those with eye-catching findings. But while coming up with eye-catching theories is relatively easy, getting reality to bear them out is another matter. The great majority collapse under the weight of contradictory data when studied rigorously. Imagine, though, that five different research teams test an interesting theory that’s making the rounds, and four of the groups correctly prove the idea false, while the one less cautious group incorrectly “proves” it true through some combination of error, fluke, and clever selection of data. Guess whose findings your doctor ends up reading about in the journal, and you end up hearing about on the evening news? Researchers can sometimes win attention by refuting a prominent finding, which can help to at least raise doubts about results, but in general it is far more rewarding to add a new insight or exciting-sounding twist to existing research than to retest its basic premises—after all, simply re-proving someone else’s results is unlikely to get you published, and attempting to undermine the work of respected colleagues can have ugly professional repercussions.

In the late 1990s, Ioannidis set up a base at the University of Ioannina. He pulled together his team, which remains largely intact today, and started chipping away at the problem in a series of papers that pointed out specific ways certain studies were getting misleading results. Other meta-researchers were also starting to spotlight disturbingly high rates of error in the medical literature. But Ioannidis wanted to get the big picture across, and to do so with solid data, clear reasoning, and good statistical analysis. The project dragged on, until finally he retreated to the tiny island of Sikinos in the Aegean Sea, where he drew inspiration from the relatively primitive surroundings and the intellectual traditions they recalled. “A pervasive theme of ancient Greek literature is that you need to pursue the truth, no matter what the truth might be,” he says. In 2005, he unleashed two papers that challenged the foundations of medical research.

He chose to publish one paper, fittingly, in the online journal PLoS Medicine, which is committed to running any methodologically sound article without regard to how “interesting” the results may be. In the paper, Ioannidis laid out a detailed mathematical proof that, assuming modest levels of researcher bias, typically imperfect research techniques, and the well-known tendency to focus on exciting rather than highly plausible theories, researchers will come up with wrong findings most of the time. Simply put, if you’re attracted to ideas that have a good chance of being wrong, and if you’re motivated to prove them right, and if you have a little wiggle room in how you assemble the evidence, you’ll probably succeed in proving wrong theories right. His model predicted, in different fields of medical research, rates of wrongness roughly corresponding to the observed rates at which findings were later convincingly refuted: 80 percent of non-randomized studies (by far the most common type) turn out to be wrong, as do 25 percent of supposedly gold-standard randomized trials, and as much as 10 percent of the platinum-standard large randomized trials. The article spelled out his belief that researchers were frequently manipulating data analyses, chasing career-advancing findings rather than good science, and even using the peer-review process—in which journals ask researchers to help decide which studies to publish—to suppress opposing views. “You can question some of the details of John’s calculations, but it’s hard to argue that the essential ideas aren’t absolutely correct,” says Doug Altman, an Oxford University researcher who directs the Centre for Statistics in Medicine.

Still, Ioannidis anticipated that the community might shrug off his findings: sure, a lot of dubious research makes it into journals, but we researchers and physicians know to ignore it and focus on the good stuff, so what’s the big deal? The other paper headed off that claim. He zoomed in on 49 of the most highly regarded research findings in medicine over the previous 13 years, as judged by the science community’s two standard measures: the papers had appeared in the journals most widely cited in research articles, and the 49 articles themselves were the most widely cited articles in these journals. These were articles that helped lead to the widespread popularity of treatments such as the use of hormone-replacement therapy for menopausal women, vitamin E to reduce the risk of heart disease, coronary stents to ward off heart attacks, and daily low-dose aspirin to control blood pressure and prevent heart attacks and strokes. Ioannidis was putting his contentions to the test not against run-of-the-mill research, or even merely well-accepted research, but against the absolute tip of the research pyramid. Of the 49 articles, 45 claimed to have uncovered effective interventions. Thirty-four of these claims had been retested, and 14 of these, or 41 percent, had been convincingly shown to be wrong or significantly exaggerated. If between a third and a half of the most acclaimed research in medicine was proving untrustworthy, the scope and impact of the problem were undeniable. That article was published in the Journal of the American Medical Association.

DRIVING ME BACK to campus in his smallish SUV—after insisting, as he apparently does with all his visitors, on showing me a nearby lake and the six monasteries situated on an islet within it—Ioannidis apologized profusely for running a yellow light, explaining with a laugh that he didn’t trust the truck behind him to stop. Considering his willingness, even eagerness, to slap the face of the medical-research community, Ioannidis comes off as thoughtful, upbeat, and deeply civil. He’s a careful listener, and his frequent grin and semi-apologetic chuckle can make the sharp prodding of his arguments seem almost good-natured. He is as quick, if not quicker, to question his own motives and competence as anyone else’s. A neat and compact 45-year-old with a trim mustache, he presents as a sort of dashing nerd—Giancarlo Giannini with a bit of Mr. Bean.

The humility and graciousness seem to serve him well in getting across a message that is not easy to digest or, for that matter, believe: that even highly regarded researchers at prestigious institutions sometimes churn out attention-grabbing findings rather than findings likely to be right. But Ioannidis points out that obviously questionable findings cram the pages of top medical journals, not to mention the morning headlines. Consider, he says, the endless stream of results from nutritional studies in which researchers follow thousands of people for some number of years, tracking what they eat and what supplements they take, and how their health changes over the course of the study. “Then the researchers start asking, ‘What did vitamin E do? What did vitamin C or D or A do? What changed with calorie intake, or protein or fat intake? What happened to cholesterol levels? Who got what type of cancer?’” he says. “They run everything through the mill, one at a time, and they start finding associations, and eventually conclude that vitamin X lowers the risk of cancer Y, or this food helps with the risk of that disease.” In a single week this fall, Google’s news page offered these headlines: “More Omega-3 Fats Didn’t Aid Heart Patients”; “Fruits, Vegetables Cut Cancer Risk for Smokers”; “Soy May Ease Sleep Problems in Older Women”; and dozens of similar stories.

When a five-year study of 10,000 people finds that those who take more vitamin X are less likely to get cancer Y, you’d think you have pretty good reason to take more vitamin X, and physicians routinely pass these recommendations on to patients. But these studies often sharply conflict with one another. Studies have gone back and forth on the cancer-preventing powers of vitamins A, D, and E; on the heart-health benefits of eating fat and carbs; and even on the question of whether being overweight is more likely to extend or shorten your life. How should we choose among these dueling, high-profile nutritional findings? Ioannidis suggests a simple approach: ignore them all.

For starters, he explains, the odds are that in any large database of many nutritional and health factors, there will be a few apparent connections that are in fact merely flukes, not real health effects—it’s a bit like combing through long, random strings of letters and claiming there’s an important message in any words that happen to turn up. But even if a study managed to highlight a genuine health connection to some nutrient, you’re unlikely to benefit much from taking more of it, because we consume thousands of nutrients that act together as a sort of network, and changing intake of just one of them is bound to cause ripples throughout the network that are far too complex for these studies to detect, and that may be as likely to harm you as help you. Even if changing that one factor does bring on the claimed improvement, there’s still a good chance that it won’t do you much good in the long run, because these studies rarely go on long enough to track the decades-long course of disease and ultimately death. Instead, they track easily measurable health “markers” such as cholesterol levels, blood pressure, and blood-sugar levels, and meta-experts have shown that changes in these markers often don’t correlate as well with long-term health as we have been led to believe.

On the relatively rare occasions when a study does go on long enough to track mortality, the findings frequently upend those of the shorter studies. (For example, though the vast majority of studies of overweight individuals link excess weight to ill health, the longest of them haven’t convincingly shown that overweight people are likely to die sooner, and a few of them have seemingly demonstrated that moderately overweight people are likely to live longer.) And these problems are aside from ubiquitous measurement errors (for example, people habitually misreport their diets in studies), routine misanalysis (researchers rely on complex software capable of juggling results in ways they don’t always understand), and the less common, but serious, problem of outright fraud (which has been revealed, in confidential surveys, to be much more widespread than scientists like to acknowledge).

If a study somehow avoids every one of these problems and finds a real connection to long-term changes in health, you’re still not guaranteed to benefit, because studies report average results that typically represent a vast range of individual outcomes. Should you be among the lucky minority that stands to benefit, don’t expect a noticeable improvement in your health, because studies usually detect only modest effects that merely tend to whittle your chances of succumbing to a particular disease from small to somewhat smaller. “The odds that anything useful will survive from any of these studies are poor,” says Ioannidis—dismissing in a breath a good chunk of the research into which we sink about $100 billion a year in the United States alone.

And so it goes for all medical studies, he says. Indeed, nutritional studies aren’t the worst. Drug studies have the added corruptive force of financial conflict of interest. The exciting links between genes and various diseases and traits that are relentlessly hyped in the press for heralding miraculous around-the-corner treatments for everything from colon cancer to schizophrenia have in the past proved so vulnerable to error and distortion, Ioannidis has found, that in some cases you’d have done about as well by throwing darts at a chart of the genome. (These studies seem to have improved somewhat in recent years, but whether they will hold up or be useful in treatment are still open questions.) Vioxx, Zelnorm, and Baycol were among the widely prescribed drugs found to be safe and effective in large randomized controlled trials before the drugs were yanked from the market as unsafe or not so effective, or both.

“Often the claims made by studies are so extravagant that you can immediately cross them out without needing to know much about the specific problems with the studies,” Ioannidis says. But of course it’s that very extravagance of claim (one large randomized controlled trial even proved that secret prayer by unknown parties can save the lives of heart-surgery patients, while another proved that secret prayer can harm them) that helps gets these findings into journals and then into our treatments and lifestyles, especially when the claim builds on impressive-sounding evidence. “Even when the evidence shows that a particular research idea is wrong, if you have thousands of scientists who have invested their careers in it, they’ll continue to publish papers on it,” he says. “It’s like an epidemic, in the sense that they’re infected with these wrong ideas, and they’re spreading it to other researchers through journals.”

THOUGH SCIENTISTS AND science journalists are constantly talking up the value of the peer-review process, researchers admit among themselves that biased, erroneous, and even blatantly fraudulent studies easily slip through it. Nature, the grande dame of science journals, stated in a 2006 editorial, “Scientists understand that peer review per se provides only a minimal assurance of quality, and that the public conception of peer review as a stamp of authentication is far from the truth.” What’s more, the peer-review process often pressures researchers to shy away from striking out in genuinely new directions, and instead to build on the findings of their colleagues (that is, their potential reviewers) in ways that only seem like breakthroughs—as with the exciting-sounding gene linkages (autism genes identified!) and nutritional findings (olive oil lowers blood pressure!) that are really just dubious and conflicting variations on a theme.

Most journal editors don’t even claim to protect against the problems that plague these studies. University and government research overseers rarely step in to directly enforce research quality, and when they do, the science community goes ballistic over the outside interference. The ultimate protection against research error and bias is supposed to come from the way scientists constantly retest each other’s results—except they don’t. Only the most prominent findings are likely to be put to the test, because there’s likely to be publication payoff in firming up the proof, or contradicting it.

But even for medicine’s most influential studies, the evidence sometimes remains surprisingly narrow. Of those 45 super-cited studies that Ioannidis focused on, 11 had never been retested. Perhaps worse, Ioannidis found that even when a research error is outed, it typically persists for years or even decades. He looked at three prominent health studies from the 1980s and 1990s that were each later soundly refuted, and discovered that researchers continued to cite the original results as correct more often than as flawed—in one case for at least 12 years after the results were discredited.

Doctors may notice that their patients don’t seem to fare as well with certain treatments as the literature would lead them to expect, but the field is appropriately conditioned to subjugate such anecdotal evidence to study findings. Yet much, perhaps even most, of what doctors do has never been formally put to the test in credible studies, given that the need to do so became obvious to the field only in the 1990s, leaving it playing catch-up with a century or more of non-evidence-based medicine, and contributing to Ioannidis’s shockingly high estimate of the degree to which medical knowledge is flawed. That we’re not routinely made seriously ill by this shortfall, he argues, is due largely to the fact that most medical interventions and advice don’t address life-and-death situations, but rather aim to leave us marginally healthier or less unhealthy, so we usually neither gain nor risk all that much.

Medical research is not especially plagued with wrongness. Other meta-research experts have confirmed that similar issues distort research in all fields of science, from physics to economics (where the highly regarded economists J. Bradford DeLong and Kevin Lang once showed how a remarkably consistent paucity of strong evidence in published economics studies made it unlikely that any of them were right). And needless to say, things only get worse when it comes to the pop expertise that endlessly spews at us from diet, relationship, investment, and parenting gurus and pundits. But we expect more of scientists, and especially of medical scientists, given that we believe we are staking our lives on their results. The public hardly recognizes how bad a bet this is. The medical community itself might still be largely oblivious to the scope of the problem, if Ioannidis hadn’t forced a confrontation when he published his studies in 2005.

Ioannidis initially thought the community might come out fighting. Instead, it seemed relieved, as if it had been guiltily waiting for someone to blow the whistle, and eager to hear more. David Gorski, a surgeon and researcher at Detroit’s Barbara Ann Karmanos Cancer Institute, noted in his prominent medical blog that when he presented Ioannidis’s paper on highly cited research at a professional meeting, “not a single one of my surgical colleagues was the least bit surprised or disturbed by its findings.” Ioannidis offers a theory for the relatively calm reception. “I think that people didn’t feel I was only trying to provoke them, because I showed that it was a community problem, instead of pointing fingers at individual examples of bad research,” he says. In a sense, he gave scientists an opportunity to cluck about the wrongness without having to acknowledge that they themselves succumb to it—it was something everyone else did.

To say that Ioannidis’s work has been embraced would be an understatement. His PLoS Medicinepaper is the most downloaded in the journal’s history, and it’s not even Ioannidis’s most-cited work—that would be a paper he published in Nature Genetics on the problems with gene-link studies. Other researchers are eager to work with him: he has published papers with 1,328 different co-authors at 538 institutions in 43 countries, he says. Last year he received, by his estimate, invitations to speak at 1,000 conferences and institutions around the world, and he was accepting an average of about five invitations a month until a case last year of excessive-travel-induced vertigo led him to cut back. Even so, in the weeks before I visited him he had addressed an AIDS conference in San Francisco, the European Society for Clinical Investigation, Harvard’s School of Public Health, and the medical schools at Stanford and Tufts.

The irony of his having achieved this sort of success by accusing the medical-research community of chasing after success is not lost on him, and he notes that it ought to raise the question of whether he himself might be pumping up his findings. “If I did a study and the results showed that in fact there wasn’t really much bias in research, would I be willing to publish it?” he asks. “That would create a real psychological conflict for me.” But his bigger worry, he says, is that while his fellow researchers seem to be getting the message, he hasn’t necessarily forced anyone to do a better job. He fears he won’t in the end have done much to improve anyone’s health. “There may not be fierce objections to what I’m saying,” he explains. “But it’s difficult to change the way that everyday doctors, patients, and healthy people think and behave.”

AS HELTER-SKELTER as the University of Ioannina Medical School campus looks, the hospital abutting it looks reassuringly stolid. Athina Tatsioni has offered to take me on a tour of the facility, but we make it only as far as the entrance when she is greeted—accosted, really—by a worried-looking older woman. Tatsioni, normally a bit reserved, is warm and animated with the woman, and the two have a brief but intense conversation before embracing and saying goodbye. Tatsioni explains to me that the woman and her husband were patients of hers years ago; now the husband has been admitted to the hospital with abdominal pains, and Tatsioni has promised she’ll stop by his room later to say hello. Recalling the appendicitis story, I prod a bit, and she confesses she plans to do her own exam. She needs to be circumspect, though, so she won’t appear to be second-guessing the other doctors.

Tatsioni doesn’t so much fear that someone will carve out the man’s healthy appendix. Rather, she’s concerned that, like many patients, he’ll end up with prescriptions for multiple drugs that will do little to help him, and may well harm him. “Usually what happens is that the doctor will ask for a suite of biochemical tests—liver fat, pancreas function, and so on,” she tells me. “The tests could turn up something, but they’re probably irrelevant. Just having a good talk with the patient and getting a close history is much more likely to tell me what’s wrong.” Of course, the doctors have all been trained to order these tests, she notes, and doing so is a lot quicker than a long bedside chat. They’re also trained to ply the patient with whatever drugs might help whack any errant test numbers back into line. What they’re not trained to do is to go back and look at the research papers that helped make these drugs the standard of care. “When you look the papers up, you often find the drugs didn’t even work better than a placebo. And no one tested how they worked in combination with the other drugs,” she says. “Just taking the patient off everything can improve their health right away.” But not only is checking out the research another time-consuming task, patients often don’t even like it when they’re taken off their drugs, she explains; they find their prescriptions reassuring.

Later, Ioannidis tells me he makes a point of having several clinicians on his team. “Researchers and physicians often don’t understand each other; they speak different languages,” he says. Knowing that some of his researchers are spending more than half their time seeing patients makes him feel the team is better positioned to bridge that gap; their experience informs the team’s research with firsthand knowledge, and helps the team shape its papers in a way more likely to hit home with physicians. It’s not that he envisions doctors making all their decisions based solely on solid evidence—there’s simply too much complexity in patient treatment to pin down every situation with a great study. “Doctors need to rely on instinct and judgment to make choices,” he says. “But these choices should be as informed as possible by the evidence. And if the evidence isn’t good, doctors should know that, too. And so should patients.”

In fact, the question of whether the problems with medical research should be broadcast to the public is a sticky one in the meta-research community. Already feeling that they’re fighting to keep patients from turning to alternative medical treatments such as homeopathy, or misdiagnosing themselves on the Internet, or simply neglecting medical treatment altogether, many researchers and physicians aren’t eager to provide even more reason to be skeptical of what doctors do—not to mention how public disenchantment with medicine could affect research funding. Ioannidis dismisses these concerns. “If we don’t tell the public about these problems, then we’re no better than nonscientists who falsely claim they can heal,” he says. “If the drugs don’t work and we’re not sure how to treat something, why should we claim differently? Some fear that there may be less funding because we stop claiming we can prove we have miraculous treatments. But if we can’t really provide those miracles, how long will we be able to fool the public anyway? The scientific enterprise is probably the most fantastic achievement in human history, but that doesn’t mean we have a right to overstate what we’re accomplishing.”

We could solve much of the wrongness problem, Ioannidis says, if the world simply stopped expecting scientists to be right. That’s because being wrong in science is fine, and even necessary—as long as scientists recognize that they blew it, report their mistake openly instead of disguising it as a success, and then move on to the next thing, until they come up with the very occasional genuine breakthrough. But as long as careers remain contingent on producing a stream of research that’s dressed up to seem more right than it is, scientists will keep delivering exactly that.

“Science is a noble endeavor, but it’s also a low-yield endeavor,” he says. “I’m not sure that more than a very small percentage of medical research is ever likely to lead to major improvements in clinical outcomes and quality of life. We should be very comfortable with that fact.”

This article available online at:

http://www.theatlantic.com/magazine/archive/2010/11/lies-damned-lies-and-medical-science/8269/

* * Department of Medicine, McGill University and McGill University Health Centre, Montreal, Quebec, Canada; and [image: {dagger}] Genzyme Corporation, Middleton, Wisconsin * The differential effects between cinacalcet and active vitamin D compounds on parathyroid function, mineral metabolism, and skeletal function are incompletely understood. Here, we studied cinacalcet and active vitamin D compounds in mice expressing the null mutation for *Cyp27b1*, which encodes 25-hydroxyvitamin D-1[image: {alpha}]-hydroxylase, thereby lacking endogenous 1,25-dihydroxyvitamin D3 [1,25(OH)2D3]. Vehicle-treated mice given high dietary calcium had hypocalcemia, hypophosphatemia, and marked secondary hyperparathyroidism. Doxercalciferol and 1,25(OH)2D3 each normalized these parameters and corrected both the abnormal growth plate architecture and the diminished longitudinal bone growth observed in these mice. In contrast, cinacalcet suppressed serum parathyroid hormone (PTH) cyclically and did not correct the skeletal abnormalities and hypocalcemia persisted. Vehicle-treated mice given a “rescue diet” (high calcium and phosphorus, 20% lactose) had normal serum calcium and PTH levels; cinacalcet induced transient hypocalcemia and mild hypercalciuria. The active vitamin D compounds and cinacalcet normalized the increased osteoblast activity observed in mice with secondary hyperparathyroidism; cinacalcet, however, increased the number and activity of osteoclasts. In conclusion, cinacalcet reduces PTH in a cyclical manner, does not eliminate hypocalcemia, and does not correct abnormalities of the growth plate. Doxercalciferol and 1,25(OH)2D3reduce PTH in a sustained manner, normalize serum calcium, and improve skeletal abnormalities.

Published ahead of print on July 22, 2010 J Am Soc Nephrol 21: 1713-1723, 2010

Free full text: http://jasn.asnjournals.org/cgi/content/full/21/10/1713

RECENTLY the doctor gave me a prescription for a week’s worth of antibiotics, along with the usual stern warning about the importance of completing the full course.

I understood why I needed to complete the full course, of course. What I didn’t understand was why a full course took precisely seven days. Why not six, eight or nine and a half? Did the number seven correspond to some biological fact about the human digestive tract or the life cycle of bacteria? As I walked out of the emergency room that night with my prescription in hand, I couldn’t help but suspect that I’d just been treated with magic.

Certain numbers have magical properties. E, pi and the Fibonacci series come quickly to mind — if you are a mathematician, that is. For the rest of us, the magic numbers are the familiar ones that have something to do with the way we keep track of time (7, say, and 24) or something to do with the way we count (namely, on 10 fingers). The “time numbers” and the “10 numbers” hold remarkable sway over our lives. We think in these numbers (if you ask people to produce a random number between one and a hundred, their guesses will cluster around the handful that end in zero or five) and we talk in these numbers (we say we will be there in five or 10 minutes, not six or 11).

But these magic numbers don’t just dominate our thoughts and dictate our words; they also drive our most important decisions.

Consider my prescription. Antibiotics are a godsend, but just how many pills should God be sending? A recent study of antibiotic treatmentpublished in a leading medical journal began by noting that “the usual treatment recommendation of 7 to 10 days for uncomplicated pneumonia is not based on scientific evidence” and went on to show that an abbreviated course of three days was every bit as effective as the usual course of eight.

My doctor had recommended seven. Where in the world had seven come from?

Italy! Seven is a magic number because only it can make a week, and it was given this particular power in 321 A.D. by the Roman emperor Constantine, who officially reduced the week from eight days to seven. The problem isn’t that Constantine’s week was arbitrary — units of time are often arbitrary, which is why the Soviets adopted the five-day week before they adopted the six-day week, and the French adopted the 10-day week before they adopted the 60-day vacation.

The problem is that Constantine didn’t know a thing about bacteria, and yet modern doctors continue to honor his edict. If patients are typically told that every 24 hours (24 being the magic number that corresponds to the rotation of the earth) they should take three pills (three being the magic number that divides any time period into a beginning, middle and end) and that they should do this for seven days, they will end up taking 21 pills.

If even one of those pills is unnecessary — that is, if people who take 20 pills get just as healthy just as fast as people who take 21 — then millions of people are taking at least 5 percent more medication than they actually need. This overdose contributes not only to the punishing costs of health care, but also to the evolution of the antibiotic-resistant strains of “superbugs” that may someday decimate our species. All of which seems like a rather high price to pay for fealty to ancient Rome.

Magic “time numbers” cost a lot, but magic “10 numbers” may cost even more. In 1962, a physicist named M. F. M. Osborne noticed that stock prices tended to cluster around numbers ending in zero and five. Why? Well, on the one hand, most people have five fingers, and on the other hand, most people have five more. It isn’t hard to understand why an animal with 10 fingers would use a base-10 counting system. But according to economic theory, a stock’s price is supposed to be determined by the efficient workings of the free market and not by the phalanges of the people trading it.

And yet, research shows that fingers affect finances. For example, a stock that closed the previous day at $10.01 will perform about as well as a stock that closed at $10.03, but it will significantly outperform a stock that closed at $9.99. If stocks close two pennies apart, then why does it matter which pennies they are? Because for animals that go from thumb to pinkie in four easy steps, 10 is a magic number, and we just can’t help but use it as a magic marker — as a reference point that $10.01 exceeds and $9.99 does not. Retailers have known this for centuries, which is why so many prices end in nine and so few in one.

The hand is not the only part of our anatomy that gives certain numbers their magical powers. The tongue does too. Because of the acoustic properties of our vocal apparatus, some words just sound bigger than others. The back vowels (the “u” in buck) sound bigger than the front vowels (the “i” in sis), and the stops (the “b” in buck) sound bigger than the fricatives (the “s” in sis). As it turns out, in well over 100 languages, the words that denote bigness are made with bigger sounds.

The sound a number makes can influence our decisions about it. In a recent study http://www.sciencedaily.com/releases/2010/01/100119111051.htm, one group was shown an ad for an ice-cream scoop that was priced at $7.66, while another was shown an ad for a $7.22 scoop. The lower price is the better deal, of course, but the higher price (with its silky s’s) makes a smaller sound than the lower price (with its rattling t’s).

And because small sounds usually name small things, shoppers who were offered the scoop at the higher but whispery price of $7.66 were more likely to buy it than those offered the noisier price of $7.22 — but only if they’d been asked to say the price aloud.

The magic that magic numbers do is all too often black. They hold special significance for terrestrial mammals with hands and watches, but they mean nothing to streptococcus or the value of Google. Which is why we should be suspicious when the steps to sobriety correspond to a half turn of our planet, when the eternal commandments of God correspond to the architecture of our paws and when the habits of highly effective people — and highly trained doctors — correspond to the whims of a dead emperor.

Source: http://www.nytimes.com/2010/10/17/opinion/17gilbert.html

Daniel Gilbert is a professor of psychology at Harvard, the author of “Stumbling on Happiness” and the host of the television series “This Emotional Life.”

The war against industry-sponsored medical education is in full tilt. In recent anti-pharma news, industry employees have been barred from giving talks during at least two important upcoming medical meetings, and oncologists from Vermont, Minnesota, and Massachusetts were forbidden from partaking in the snacks provided at corporate exhibit booths during a recent annual cancer society meeting. These developments come on the heels of a movement already well under way at medical centers around the country: ending the free lunch.

Every year, the pharmaceutical industry spends billions of dollars on educational programs for doctors, many of them involving food and drinks. Doctors who are experts on a new medication are paid handsomely by the drug’s maker to speak to other doctors—over a fancy dinner or a casual lunch—about updates on treating a particular disease that (no surprise here) the new drug just so happens to treat. This approach isn’t the only way that doctors continue their post-med-school education, but it is a mainstay, and not just because of the free and tasty grub. These sessions help move the latest medical advances out of the lab and into daily practice.

But with the mounting concern about ties between doctors and the pharmaceutical industry, commercially supported medical education is being axed from hospitals and university medical centers around the country. Not only is this change unfortunate for anyone with a doctor, but it also doesn’t make any sense.

When the FDA approves a new drug, the package label notes a very specific indication, and pharmaceutical companies may only market the drug for that purpose. But often the appropriate use, or standard of care, differs from the use the FDA approved. For example, when Remicade was first marketed for the treatment of Crohn’s disease, the approved, or on-label, indication was a single intravenous infusion. In reality, Remicade needs to be given on a continual, long-term basis. Patients given a single infusion quickly develop antibodies against the drug, resulting in an allergic reaction on subsequent exposure. But a long-term trial would have delayed getting it to patients in need—Remicade was a much better treatment than what was already available for Crohn’s. So although the well-respected doctors who served as trial investigators knew that routine use of Remicade needed to be long-term, they decided to submit the single-dose data for regulatory review. The FDA regulates how a drug is marketed, not how it’s used by doctors. While Remicade’s manufacturers couldn’t advertise the drug for long-term use, trial investigators could demonstrate the appropriate, off-label, use. For several years, gastroenterologists from the world’s top medical centers, who’d been part of Remicade’s development since its inception, traveled around the world, instructing doctors on how to use the drug.

That practical knowledge could never have been gleaned from a journal article or the package insert. Generally, the published reports of clinical trials present complicated statistical analyses about a drug’s likelihood to benefit patients. They don’t teach how to use the drug. Physicians needed in-person training. They needed to hear an expert discuss the ins and outs of a new medication—what side effects to expect, how to manage them, how long to wait between infusions, when dose adjustments might be needed. That was the only way to ensure the optimal treatment of patients with Crohn’s disease. Most, if not all, of those sessions were paid for by the drug’s maker and often included food and drinks.

But sessions like this—meetings with key opinion leaders over lunch, dinner, or a snack to discuss the latest advances in treating this or that condition—are being banned left and right. Since at least June of 2009, the University of Pittsburgh, Mount Sinai School of Medicine, Stanford University School of Medicine, Johns Hopkins School of Medicine, and several other prominent institutions have prohibited industry-funded meals. Politicians and other federal overseers are concerned that commercially supported medical education leads to misuse of drugs—in particular, that doctors who have enjoyed a meal on the pharmaceutical company’s tab will prescribe an expensive drug even if it is not the best treatment option. Like that curl of smoke carrying an irresistible scent in an old cartoon, pharma-provided victuals, the thinking goes, woo doctors into mindless, expensive prescribing.

But cauterizing industry-sponsored education leaves a huge gap in care. Stephen Hanauer, one of the clinical investigators who developed Remicade and who has been paid to speak to doctors about it, explains that as Remicade teaching sessions have been nixed, misuse of the drug has risen—and Hanauer thinks that the two phenomena are connected. Hanauer now regularly sees Crohn’s disease patients who were treated inappropriately with Remicade. Uneducated about its off-label use, the physicians gave the drug as a single infusion, which led to resistance, leaving patients with very limited treatment options. The investigators also discovered that breaks between doses need to be kept short, but many gastroenterologists haven’t had the chance to learn that, resulting in unnecessary sickness.

Many drugs are used off-label on a regular basis. Clinical trials are done in a vacuum, and even when the standard-of-care use does not differ quite so starkly from the on-label use, doctors still require hands-on learning. Right now, the most effective way to do that is through commercially supported medical education so that the speakers can be paid and the session can be done in a way that works within doctors’ busy schedules.

But surely there must be other options. Can’t doctors meet with the experts in the absence of fancy cheese? Not necessarily. Teaching sessions often take place during the lunch hour. As Hanauer, who practices at the University of Chicago School of Medicine, describes, the elimination of paid lunches sent hungry doctors to the cafeteria instead of the lecture hall. “But the lines were so long that they missed the conference,” he says. “So attendance at our grand rounds conferences went to miniscule.” Now the doctor has a sandwich but isn’t up to date on how to treat a serious disease. That may sound silly, but it’s often the mundane reality. “There are sometimes times when residents have to choose between lunch and a conference,” Richard Goldberg, an oncologist at the University of North Carolina, wrote in an e-mail.

The backlash against commercial support has also led many prominent medical centers to ban faculty from receiving significant amounts of industry dollars for teaching and consulting. But these professors are often the top experts in their field, the ones at the research helm. Promotional talks given by drug reps—who are company employees, not doctors—are monitored by the FDA, and any discussion of off-label use is strictly prohibited. That’s for good reason; the only people telling doctors how to use a drug should be doctors who know how to use the drug. But if these doctors are prohibited from giving talks, then how is that going to happen?

Continuing medical education programs are another option. The pharmaceutical industry spends more than $1 billion a year on educational programs that are also CME-certified (see Table 6 here)—that is, doctors attending them can earn the credit hours they need in order to keep their medical licenses. These programs do permit off-label discussion of drugs. However, CME guidelines are strict. Programs must present a balanced view of all treatment options for a given disease, and pharmaceutical companies may not influence the program.

Fair enough. Companies shouldn’t be able to determine the content of any educational program, especially one that qualifies for CME credit. But as this wall has thickened, pharma has pulled away from funding CME programs, which means fewer free educational opportunities for doctors. Unsponsored, in-person CME programs can cost hundreds to thousands of dollars, which starts to pinch the wallet, even for doctors, who aren’t all loaded. The reluctance stems not only from the lack of opportunity to influence doctors but also fear of being seen as promoting a drug. Many companies have decided it’s just not worth the risk or trouble. Besides, some universities are already pushing industry out of CME programs, too.

Without programs being brought to their door, most doctors will get their necessary credits in one fell swoop at their specialty’s annual conference, which offer CME sessions. But an hour-long talk in a giant lecture hall is hardly the intimate atmosphere truly needed to learn about a new drug. More than 30,000 people attended the recent annual meeting of the American Society of Clinical Oncology, the largest meeting for cancer health care professionals. Presenting new drug data to an audience of thousands precludes the pertinent dialogue that’s possible in a smaller setting. And waiting until the annual meeting rolls around doesn’t seem like the best way to stay on top of the latest developments. Furthermore, the balanced nature of CME programs often leads to a very watered-down presentation of cutting-edge advances. A seminar may present several speakers discussing multiple treatments for a disease without honing in on the specifics of using one essential new tool. The content, the size, and the impersonal nature of these talks don’t deliver the level of detail that doctors must know as they inject a new foreign substance into a living, breathing human.

The same goes for the plethora of online videos and other materials produced without commercial support. There is no substitute for a small group of people listening to a doctor talk about how to treat a disease. And there is no substitute for the commercial support required to run such programs.

In a recent study, academic researchers were paid a modest honorarium to travel around the country teaching more than 14,000 doctors about new treatment guidelines for high blood pressure. Each researcher met with small groups of doctors to educate them about the latest advances. In counties where the most sessions took place, adherence to the guidelines rose by more than 8 percent. In counties with the fewest such sessions, adherence decreased by 2 percent. The approach that the pharmaceutical industry has been taking for years is actually an effective way to educate doctors.

The concern about industry’s influence over medical care is obviously well-founded. There are plenty of cases in which doctors have promoted unproven off-label use or have become unduly biased toward prescribing a drug that they learned about through a pharma-paid program. And it’s doubtful that companies would shell out so much money if their bottom lines didn’t stand to benefit.

But the entanglement caused by for-profit drug development can’t be undone by eliminating the free lunch. As one physician suggested, perhaps pharmaceutical companies should be required to pay for medical education. After all, if companies are going to unleash new drugs into the world, shouldn’t they be responsible for teaching people how to use it? Ousting commercial support is creating a huge chasm in medical education, leaving doctors not only hungry but also starved for knowledge. __________________________________________________________________________ Jessica Wapner, based in New York, writes frequently about health care and biomedical issues.

Article URL: http://www.slate.com/id/2257785/