A new online tool to improve Alzheimer's clinical trials recruitment

by National Institute on Aging

The newly launched Outreach Pro, a tool for Alzheimer’s researchers who need to create and customize recruitment resources such as websites, handouts, videos, and social media posts. Credit: NIH National Institute on Aging

The National Institute on Aging (NIA), part of the National Institutes of Health (NIH), has launched a new online research tool to help increase participation by traditionally underrepresented populations in clinical trials on Alzheimer's disease and related dementias. Unveiled at the Alzheimer's Association International Conference (AAIC), Outreach Pro enables those involved with leading clinical research to create and customize participant recruitment communications such as websites, handouts, videos, and social media posts.

03 aug 2021--"We are facing a critical and growing need for people living with Alzheimer's and related dementias, as well as those at higher risk, and healthy people, to participate in clinical trials," said NIA Director Richard J. Hodes M.D. "That need is especially acute for frequently underrepresented groups such as Black and Hispanic Americans, which is why Outreach Pro includes an emphasis on helping clinical trial researchers connect with these and other important communities."

Outreach Pro is an integral part of NIA's efforts to implement the National Strategy for Recruitment and Participation in Alzheimer's and Related Dementias Clinical Research. Released in 2018, the national strategy was developed in collaboration with the Alzheimer's Association with input from government, private sector, academic, and industry stakeholders, as well as from individuals, caregivers, and study participants. The overarching goal is to engage broader segments of the public, including underrepresented populations, to participate in Alzheimer's and related dementias clinical research.

"It is critical that clinical trials have appropriate representation to ensure we have a complete understanding of how well different therapies or approaches to dementia care work in different populations," said Holly Massett, Ph.D., NIA senior advisor on clinical research recruitment and engagement, who oversees the implementation of the national strategy. "Outreach Pro was designed to provide well-tested and culturally appropriate outreach materials that resonate with diverse populations and encourage them to participate in clinical trials."

To use Outreach Pro, researchers and clinicians first select desired templates with one of three communication goals in mind: 1) to educate about Alzheimer's, related dementias, and/or brain health; 2) to increase awareness and interest in Alzheimer's and related dementias clinical trials; or, 3) to provide information about a specific Alzheimer's or related dementias clinical trial currently enrolling participants. Each template can then be tailored using a central library of messages, headlines, photos, and text that have been extensively tested among individuals representing diverse and underserved populations.

Outreach Pro's current library of content includes materials specifically designed for a range of audiences, including Black Americans and Hispanics/Latinos. Initially, the materials will be available in English and Spanish, and there are plans underway to add Asian American and Pacific Islander resources and languages by fall 2021. Materials for American Indian and Alaska Native communities will be developed and added in 2022.

NIA developed Outreach Pro and its content systematically by using literature reviews, environmental scans, listening sessions with stakeholders, focus groups, national surveys, and user testing. The NIA team created tool features in a culturally responsive way, so that all stages of content development reflect the culture and languages of the communities for whom the materials are designed. NIA plans to add content and scale up the tool's capabilities based on feedback and performance measurement.

Outreach Pro expands NIA's resources dedicated to recruitment diversity. For example, in 2020, NIA funded four exploratory Alzheimer's Disease Research Centers that will broaden research initiatives with underrepresented groups, including Black Americans, Native Americans, and those in rural communities. In 2019, NIA launched the Alzheimer's and Dementia Outreach, Recruitment, and Engagement (ADORE) Resources. The ADORE repository offers the research community resources to support recruitment and retention of volunteers into clinical trials and studies.

In total, NIA is supporting 270 Alzheimer's and related dementias clinical trials, including those focused on lifestyle and caregiving interventions. Late-stage trials often include thousands of participants, requiring even more volunteers to help researchers meet recruitment goals for diversity.

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More information: Outreach Pro: outreachpro.nia.nih.gov/

Volunteer gateway: www.alzheimers.gov/taking-action/volunteer

The fascinating history of clinical trials

by Adrian Esterman, The Conversation

Credit: CC0 Public Domain

Clinical trials are under way around the world, including in Australia, testing COVID-19 vaccines and treatments.

06 jun 2020--These clinical trials largely fall into two groups. With observational studies, researchers follow a group of people to see what happens to them. With experimental studies, people are assigned to treatments, then followed.

These study designs have come about from centuries of people trying out different ways of treating people.

Here are some of the key moments in the history of clinical trials that led to the type of trials we see today for COVID-19.

Ginseng in 11th-century China

One of the earliest observational studies occurred nearly 1,000 years ago in China. The 1061 Atlas of Materia Medica (Ben Cao Tu Jing) was compiled and edited by Song Su, a renowned scientist, administrator, diplomat and military strategist.

It documented a trial of ginseng: "[…] to evaluate the effect of genuine Shangdang ginseng, two persons were asked to run together. One was given the ginseng while the other ran without. After running for approximately three to five li [about 1,500-2,500 metres], the one without the ginseng developed severe shortness of breath, while the one who took the ginseng breathed evenly and smoothly."This observational study is also the first recorded example of a control group.

A control group can be patients who are not treated at all, patients who receive a standard treatment compared to a new one, or patients who receive a placebo (a treatment or substance designed to have no therapeutic effect).

Having a control group is one of the cornerstones of modern clinical trials.

An example of a control group in COVID-19 research is this recent study. People with diabetes hospitalised for COVID-19 were divided into those receiving the drug metformin and those not receiving it (the control group).

Back to ginseng. Today, it is a popular herbal remedy. As to whether it improves stamina, a recent review found some evidence ginseng might help men with erectile dysfunction.

Rhubarb in 18th-century England

Rhubarb roots have been used as a laxative for more than 5,000 years, including in 18th-century England.

Caleb Parry, an English physician working in Bath, wanted to know whether locally grown rhubarb was as good as the more expensive Turkish variety.

In 1786, he ran a study in which he switched the type of rhubarb he gave to each patient at different times. He then compared each patient's symptoms while eating each type of rhubarb. He concluded there was no advantage in using the Turkish version.

This is the first published example of a crossover trial (a study where the participants receive each treatment at different times).

Today, we know rhubarb roots and stems are rich in anthraquinones, which have a laxative effect.

Early 20th-century randomised trial

Beriberi, a disease that can have lasting effects on the nervous system and heart, was common in Southeast Asia in the early part of the 20th century.

In 1905 a beriberi outbreak occured at the Kuala Lumpur Lunatic Asylum. At that time William Fletcher was the district surgeon. He realised the outbreak provided an excellent opportunity to run an experiment (which we now know is just a bit unethical).

Each patient was assigned a number. Those with even numbers were sent to one ward and given brown unpolished rice to eat. Those with odd numbers went to another ward and given white polished rice.

At the end of the experiment, 15% of the patients who ate the white rice died of beriberi; none given brown rice died.

This is a very early example of randomisation in a clinical trial, where one group is chosen at random to receive a treatment.

Randomisation is another very important factor in good clinical trial design.

Today we know beriberi is caused by a deficiency in thiamine (vitamin B1) and a white rice diet is deficient in thiamine.

Tuberculosis and the randomised controlled trial

Sir Austin Bradford Hill, an English epidemiologist and statistician, conducted the first randomised controlled trial in 1948. The trial was to treat the lung disease tuberculosis.

Bradford Hill decided whether a patient should be treated with the antibiotic streptomycin plus bed rest, or bed rest alone, by using a table of random numbers.

The investigators didn't know which patient got each treatment; details were in sealed envelopes. Patients were not told they were in a trial.

Using sealed envelopes is an example of what we now call allocation concealment. Making sure neither investigators nor patients know which treatment they are receiving is called blinding. These are now standard features of randomised controlled trials.

Randomised controlled trials are the "gold standard" of clinical trial designs, due to the use of both a control group and randomisation.

Decades later, researchers have used a randomised controlled trial to test the drug ruxolitinib in patients with severe COVID-19.

So, although Bradford Hill conducted the first randomised controlled trial, it was based on hundreds of years of people working out why things like a control group and randomisation are so important.

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Provided by The Conversation 

We're doing drug trials wrong – here's how to fix it

Credit: Jason Salmon/Shutterstock.com

By the age of 65, at least half of us will suffer from two or more long-term diseases. And the chance of having multi-morbidity, as it is known, increases with age.
Only 9% of people with coronary heart disease have no other condition. The other 91% have various combinations of hypertension (high blood pressure), heart failure, stroke, diabetes, chronic obstructive pulmonary disease, depression, dementia, chronic kidney disease and so on.

22 oct 2018--And it's not just the elderly who suffer from several long-term conditions – young people do too. In poor areas, the occurrence of two or more diseases in the young can occur ten to 15 years earlier compared with those in wealthier regions.
People with multi-morbidities have to take a range of drugs: one or more for each disease. But whether drugs developed to treat single diseases are effective in patients with multi-morbidity is a matter of debate. In some patients, their body attacks the drug as though it were a pathogen. In other patients, the treatment causes [side effects] that are worse than the disease being treated, including an increased risk of infection.
A new class of drugs, so-called disease-modifying anti-rheumatic drugs, are being used to treat rheumatoid arthritis. These drugs treat the underlying disease rather than just ease the symptoms. This is a major advance, but at least 40% of the people taking them won't see an improvement in their symptoms. This is probably because most patients have another disease, which may stop the drug working properly.
The root of the problem in developing all new medicines lies in the tendency to research, diagnose and treat diseases as a single entity. The single disease approach goes right back to the way biology is taught at school and university.

Multi-morbidity is the norm

A growing number of medical researchers think we should learn from disease combinations. This may seem like an impossible task, given the number of possible combinations, but some combinations are very common, such as heart disease and high blood pressure. And not taking multi-morbidities into account affects every stage of introducing a new drug, from its discovery to testing it in patients.
The decision to develop a new drug is based on the careful analysis of thousands of patient groups. But these groups are not divided based on the presence of other existing diseases. By not grouping patients based on pre-existing conditions, many relevant new drugs specific for particular disease combinations may be missed.
Once new drugs have been developed, they are first tested in animal models of a particular disease or in tissue culture, containing an individual cell type. There is no guarantee that this type of test is relevant for human disease, and there is also no guarantee that relevant drugs won't be missed that might have worked in more complex disease combinations.
Multi-morbidities are also not taken into account when new drugs are tested in patients. Remarkably, the patients who have the most severe disease combinations, and are the most problematic to treat, are mostly excluded from clinical trials. In coronary heart disease, for example, on average, 69% of patients with multi-mobidities are excluded from clinical trials because clinicians are wary of making their disease even worse. Yet these are the patients that most need the treatment. Also, how the drug works may differ in patients with one disease compared with patients with more than one disease.
The situation is even worse for dementia patients where 95% have other diseases, yet in 86% of trials, patients with other conditions are excluded. Instead, recruitment for clinical trials picks those patients who are potentially less affected by the disease in question, as they do not have any of the commonly associated multi-morbidities, which could also mean they are in a younger age group that responds differently to the drug.

Appetite for a new approach

Is it any wonder that little progress has been made in the treatment of the most debilitating conditions affecting the human race? New targets for drugs should not be chosen irrespective of what else is wrong with the patient. Rather patients with a particular disease should be sub-categorised and studied based on the other diseases they have, and treatment specifically tested and tailored to their needs.
Also, science funding bodies and the pharmaceutical industry should drive the development of new animal and tissue culture models in which to test new drugs that encompass patient diseasecomplexity. There is an appetite among researchers for this approach, but the momentum needs to increase.

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Provided by The Conversation

Results from many large clinical trials are never published

A new analysis of 585 large, randomized clinical trials registered with ClinicalTrials.gov finds that 29 percent have not been published in scientific journals. In addition, nearly 78 percent of the unpublished trials had no results available on the website, either.

30 oct 2013--As a result, nearly 300,000 people who were enrolled in the 171 unpublished trials "were exposed to the risks of trial participation without the societal benefits which accompany the dissemination of trial results," said Christopher W. Jones, MD, a former resident physician at University of North Carolina School of Medicine who is now an attending physician at Cooper Medical School of Rowan University in Camden, N.J. and lead author of the study published in the Oct. 29, 2013 issue of the British Medical Journal.

Non-publication of clinical trials has been a controversial issue in recent years. In particular, industry-funded clinical trials – such as those paid for by pharmaceutical companies – have come under fire on allegations that such trials are often not published when the results are not favorable to the drug or other product being tested.

Against this background, the study authors set out to determine what happened to 585 large, randomized trials with at least 500 participants that were registered with ClinicalTrials.gov and completed before January 2009. ClinicalTrials.gov is a website that provides patients, their family members, health care professionals, researchers and the public with easy access to information on publicly and privately supported clinical studies on a wide range of diseases and conditions.

Of the 585 registered trials, 171 (29 percent) had not been published by November 2012, when the final literature search for this study was conducted. Non-publication was more common among trials that received industry funding (32 percent ) compared to those without industry funding (18 percent). Of the 171 unpublished trials, 133 (78 percent) had no results available in ClinicalTrials.gov.

"Clinical trials are an essential source of information for how to care for patients. Additional policies are needed to ensure that results of all large clinical trials are made publicly available in a timely manner," said Timothy F. Platts-Mills, MD, an assistant professor of emergency medicine at UNC and senior author of the study.

Provided by University of North Carolina Health Care

Limiting the problem of missing data urged for clinical trials

Missing data compromise inferences from clinical trials, and due to the problematic nature of compensation with analysis methods, the importance of avoiding missing data in clinical trials is paramount, according to a special report published in the Oct. 4 issue of the New England Journal of Medicine.

05 oct 2012—Data missing from clinical trials can undermine the credibility of those trials, and little attention has been focused on this issue until recently, experts say.

Even regulatory guidelines that direct how clinical trials should be run offer little advice on dealing with missing information, according to a new report from an expert panel commissioned by the National Research Council.

And, while statisticians may be able to control for the missing data, they can end up making "assumptions about what the outcomes would've been, and when you're doing a phase 3 clinical trial [that could lead to a drug's regulatory approval or denial], people don't want to make assumptions. They want to assure balance, which argues for trying to limit the amount of missing data," said the panel chairman, Rod Little, a biostatistics professor at the University of Michigan School of Public Health in Ann Arbor.

Another panel member, Kay Dickersin, who directs the Center for Clinical Trials and the U.S. Cochrane Center at the John's Hopkins Bloomberg School of Public Health in Baltimore, agreed. "When data are missing from clinical trials, the findings become questionable or of no use. Why are the data missing? Is it because the people with data missing all got better? All got worse? We don't know why the data are missing, and so we cannot even guesstimate what the true findings of the study would be would be if no data were missing," Dickersin said. 
"The main point is that it is far better to prevent missing data than to try to 'fix' the problem in the analysis," she added.

Findings from the panel are published as a special report in the Oct. 4 issue of the New England Journal of Medicine.

In May, a study published in the Journal of the American Medical Association also took clinical trials to task, finding that many are small and of poor quality. That study found that cancer treatment trials often failed to follow the highest standards.

To address the potential problems stemming from missing data in clinical trials, the U.S. Food and Drug Administration requested that the National Research Council convene an expert panel in 2008. The current report focuses primarily on phase 3 clinical trials assessing the safety and efficacy of drugs, biologic products and some medical devices.

Missing data was defined by the panel as information that would have been meaningful to the results of the trial.

The panel found that a major cause of missing data is participants who stop taking their assigned treatment because it's not working, the side effects are troubling or the drug regimen is too inconvenient.

But the panel suggested that researchers should continue to gather follow-up information on them anyway.

"People have the right to discontinue any treatment, but often people don't follow-up. The panel is making the point that in a lot of situations, it's useful to get that information," said Little.

Dickersin said another issue is missing data even when follow-up visits were kept. "Sometimes patients may attend their follow-up visits, but not answer all the questions they were asked. So if, for example, some people in a study about pain fail to fill in their diaries about daily pain, then we may not know that pain relief is only for a short time with the test drug when long-term pain relief is what patients are seeking," she said.

The panelists outlined a number of steps that could be taken to limit the amount of missing data in clinical trials. They include: 

• Conducting a brief run-in period in which all participants are assigned an active drug to see who can tolerate it.
• Allowing the use of rescue medications as part of the treatment regimen, so these drugs are accounted for in the analysis.
• Targeting a group that doesn't have enough current treatment options, because they have more incentive to stay in the trial.
• Shortening the follow-up period.

The panel also recommended changes in the statistical analysis of missing data at the end of the study. Little said some of the current methods used may be too simplistic.

The bottom line, he said, is that "we want to make the best possible decisions about which drugs are effective and safe."

Dickersin added, "Study participants are making an incredibly important contribution to current and future health care by participating in clinical trials. They can contribute to the impact of the findings by ensuring that they follow the protocol as asked. 
"And, even when they have to change treatments or stop the treatment to which they were assigned—say, because of side effects—they still can help the study's success by returning for visits and completing all study forms and questionnaires," she added.

More information: Full Text (subscription or payment may be required)

F.D.A. Is Lax on Oversight During Trials, Inquiry Finds

By GARDINER HARRIS
13 jan 2009--The Food and Drug Administration does almost nothing to police the financial conflicts of doctors who conduct clinical trials of drugs and medical devices in human subjects, government investigators are reporting.

Moreover, the investigators say, agency officials told them that trying to protect patients from such conflicts was not worth the effort.

In 42 percent of clinical trials, the agency did not receive forms disclosing doctors’ financial conflicts and did nothing about the problem, according to the investigation, which was conducted by the inspector general of the Department of Health and Human Services and whose results were scheduled to be made public Monday.

In 31 percent of the trials in which the agency did receive the required forms, agency reviewers did not document that they looked at the information. And in 20 percent of the cases in which doctors revealed significant financial conflicts, neither the F.D.A. nor the sponsoring companies took any action to deal with the conflicts, the investigators found.

Karen Riley, a spokeswoman for the F.D.A, said the agency opposed reviewing doctors’ financial conflicts before trials because they represented just one possible source of bias.

A similar investigation by the inspector general last year found that the National Institutes of Health did almost nothing to police the financial conflicts of university professors who received federal money. And like their colleagues at the F.D.A., officials at the health institutes said they did not want to start doing so, that investigation found.

The inquiries feed a growing debate about how money that doctors routinely collect from drug and device makers may hurt patients and skew studies.

In 1999, the agency required drug and device companies to disclose the financial conflicts of doctors overseeing patient care in clinical trials. The rules require companies to collect this information before the start of any trial and to consult with the F.D.A. to resolve serious conflicts.

But the inspector general found that the agency had done almost nothing to enforce these rules or even to use the information generated.

Fewer than 1 percent of the doctors who helped oversee clinical trials registered with the agency and who filed the required financial disclosure forms reported that they had a significant conflict of interest. By contrast, studies have found that one-fifth to one-third of all doctors have such conflicts.

“This represents 206 of the 29,691 clinical investigators listed in financial interest forms,” the report says. “Of these 206 clinical investigators, almost all disclosed only one financial interest.”

Since the F.D.A. does not have a complete list of all clinical investigators, the agency has no way of knowing whether every doctor who is required to file a form actually did so.

The rules allow drug and device makers to avoid reporting doctors’ financial conflicts if the companies certify that they tried diligently to get the information but could not. Companies cited this exemption in 28 percent of drug and device applications, the inspector general found. But in an additional 23 percent of applications, companies filed neither an exemption nor the appropriate disclosure forms.

The inspector general recommended that the F.D.A. do a better job of making sure that companies follow the rules regarding financial disclosures, that agency reviewers actually read these disclosures, and that all of this is done before trials take place so patients are protected.

But the report said the agency replied that collecting and checking this information before the trials was not worth the effort for either the companies or the agency, even though the agency’s own rules required it.

Steps could get more seniors into clinical trials

By Joene Hendry
04 oct 2008--Various strategies could encourage elderly people to participate and stay in clinical trials -- a pressing issue as the population ages -- researchers suggest.
"No one is ever too old to make a meaningful contribution to research," said Dr. Patricia S. Goode, of the University of Alabama at Birmingham.
Nevertheless, "Older participants are often specifically excluded from clinical trials, even those testing therapies that will be prescribed for older persons," Goode told Reuters Health.
She and her colleagues note in the Journal of the American College of Surgeons that trials testing different medical treatments need to recruit participants representing the people for whom the treatment is intended.
To assess potential reasons why the elderly are often excluded from research studies, the team examined the recruitment and retention of older women participating in two trials assessing surgical procedures for pelvic organ prolapse.
The investigators developed a questionnaire that addressed factors that either facilitated or impeded trial enrollment and completion, then assessed responses from 23 physicians and 11 nurses involved in research studies.
These responses show a third of the doctors and nurses felt it is harder to recruit older study participants and more than half cited difficulties obtaining informed consent.
Other hurdles for elderly participants included caregiver involvement, having several health disorders, fatigue, and cognitive impairment.
However, when Goode and colleagues assessed actual retention rates of the 512 women enrolled in the two surgical trials -- of whom about 221 were 70 years and older -- they found older participants did not have higher drop-out rates than younger participants. The investigators also noted no age-group differences in missed follow-up visits.
"Recruitment and retention of older women for research studies can equal that of younger women if special measures are taken," Goode said.
She and her colleagues list numerous steps that can be taken to overcome barriers faced by elderly participants. These include, for example, allocating time to explain study procedures clearly, ensuring participants have transportation assistance to and from study visits, buying a lightweight amplifying headset for the clinic to help people with hearing impairment, and using large print on questionnaires.
Although these strategies haven't been tested, the researchers say they could help investigators successfully enroll and retain older subject in their clinical trials.
SOURCE: Journal of the American College of Surgeons, September 2008.

Publication of Clinical Trials Supporting Successful New Drug Applications: A Literature Analysis

by Kirby Lee
28 sept 2008--The United States (US) Food and Drug Administration (FDA) approves new drugs based on sponsor-submitted clinical trials. The publication status of these trials in the medical literature and factors associated with publication have not been evaluated. We sought to determine the proportion of trials submitted to the FDA in support of newly approved drugs that are published in biomedical journals that a typical clinician, consumer, or policy maker living in the US would reasonably search.

Methods and Findings
We conducted a cohort study of trials supporting new drugs approved between 1998 and 2000, as described in FDA medical and statistical review documents and the FDA approved drug label. We determined publication status and time from approval to full publication in the medical literature at 2 and 5 y by searching PubMed and other databases through 01 August 2006. We then evaluated trial characteristics associated with publication. We identified 909 trials supporting 90 approved drugs in the FDA reviews, of which 43% (394/909) were published. Among the subset of trials described in the FDA-approved drug label and classified as “pivotal trials” for our analysis, 76% (257/340) were published. In multivariable logistic regression for all trials 5 y postapproval, likelihood of publication correlated with statistically significant results (odds ratio [OR] 3.03, 95% confidence interval [CI] 1.78–5.17); larger sample sizes (OR 1.33 per 2-fold increase in sample size, 95% CI 1.17–1.52); and pivotal status (OR 5.31, 95% CI 3.30–8.55). In multivariable logistic regression for only the pivotal trials 5 y postapproval, likelihood of publication correlated with statistically significant results (OR 2.96, 95% CI 1.24–7.06) and larger sample sizes (OR 1.47 per 2-fold increase in sample size, 95% CI 1.15–1.88). Statistically significant results and larger sample sizes were also predictive of publication at 2 y postapproval and in multivariable Cox proportional models for all trials and the subset of pivotal trials.

Conclusions
Over half of all supporting trials for FDA-approved drugs remained unpublished 5 y after approval. Pivotal trials and trials with statistically significant results and larger sample sizes are more likely to be published. Selective reporting of trial results exists for commonly marketed drugs. Our data provide a baseline for evaluating publication bias as the new FDA Amendments Act comes into force mandating basic results reporting of clinical trials.

Redefining Quality — Implications of Recent Clinical Trials

Harlan M. Krumholz, M.D., and Thomas H. Lee, M.D.
08 june 2008--Simple approaches to patient care are better — except when they are not. Recent clinical studies are leading to a reexamination of the paradigm whereby efforts to prevent vascular disease focus on the achievement of particular levels of risk factors such as low-density lipoprotein (LDL) cholesterol, systolic blood pressure, and glycated hemoglobin. Although these factors and their levels are important determinants of the development and progression of vascular disease, it is increasingly apparent that the specific strategies used to modify them make a critical difference in patient outcomes. This insight has implications for clinical practice, performance measurement, and regulatory requirements.
The conventional wisdom, which emerged from epidemiologic studies of risk factors and the subsequent successful trials of certain strategies for risk-factor modification, has been that the clinician's key focus ought to be on reducing risk factors below specific levels. This approach, however, neglects the importance of which specific strategies are used to modify these factors. A clinical trial is ultimately a test of a strategy, and we should not be surprised that different strategies may have different effects on patients beyond their effect on risk-factor levels.
Awareness of this issue was boosted on December 2, 2006, the day Pfizer stopped the study named ILLUMINATE (Investigation of Lipid Level Management to Understand Its Impact in Atherosclerotic Events) and all other trials involving torcetrapib, which until then had been seen as a promising agent that lowered LDL cholesterol levels and raised high-density lipoprotein (HDL) cholesterol levels. ILLUMINATE was halted because patients receiving torcetrapib plus atorvastatin had a higher mortality rate than those receiving atorvastatin alone — despite 72% increases in HDL levels and 25% decreases in LDL levels.1
ILLUMINATE is not alone in raising questions about the wisdom of patient care that prioritizes target levels of some risk factors over attention to the way in which those levels are achieved. The Women's Health Initiative revealed that hormone-replacement therapy, which reduces LDL cholesterol levels, increased the risk of cardiovascular disease.2 Another study, called ENHANCE (Effect of Combination Ezetimibe and High-Dose Simvastatin versus Simvastatin Alone on the Atherosclerotic Process in Patients with Heterozygous Familial Hypercholesterolemia), showed that ezetimibe did not reduce the progression of arteriosclerosis when combined with simvastatin, as compared with simvastatin alone, even though the combination did result in a greater reduction of LDL cholesterol. Rosiglitazone improves glucose control, but it may also be associated with increased cardiovascular risk.3 Adding an angiotensin-receptor blocker to an angiotensin-converting–enzyme inhibitor may produce a greater reduction in blood pressure, but it may not reduce cardiovascular risk and it increases the risk of other adverse events.4
The importance of understanding clinical trials as tests of strategies has assumed even greater prominence because of two studies being reported on in this issue of the Journal — ACCORD (Action to Control Cardiovascular Risk in Diabetes) and ADVANCE (Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation). These two studies (pages 2545–2559 and 2560–2572, respectively) tested the hypothesis that specific strategies involving the use of multiple medications to achieve tight glucose control would improve outcomes in patients with type 2 diabetes mellitus. The studies, which used different pharmacologic strategies, found that the tight control achieved did not reduce the risk of macrovascular complications. The ACCORD study's intensive control strategy was associated with a higher risk of death, which led to early discontinuation of this part of the study. The ADVANCE study's findings indicate that its strategy may reduce the risk of worsening renal function at the cost of an excess risk of hypoglycemic events.
Thus, the risk–benefit ratio of interventions designed to modify risk factors can vary depending on the type and number of medications and other approaches that are concurrently incorporated. In particular, some medications may have beneficial or harmful effects beyond their effect on a risk factor. Moreover, the strength of the evidence supporting particular strategies varies. Some strategies are known to improve patient outcomes, whereas others are known to affect only risk-factor levels or other intermediate outcomes. We are now beginning to appreciate that a strategy's effect on a risk factor may not predict its effect on patient outcomes.
Clearly, the way in which risk factors are modified really does matter. Lifestyle interventions may have few risks, but we cannot assume the same for drugs — and drug-related risks are not always known or appreciated. For example, the tendency of torcetrapib to cause blood pressure to rise and potassium levels to fall attracted much more attention after December 2006 than it had previously. In addition, medications may have interactions with other drugs, either directly or through their effect on patient adherence to treatment regimens.
As a result of these research advances, clinicians are now in a quandary. We prefer our clinical practice to be based on strong evidence. In the interest of promoting good care, we have constructed guidelines and performance measures that encourage treatment geared toward achieving ambitious goals for levels of glycated hemoglobin, lipids, and blood pressure. These treatment goals generally do not specify the strategy that should be used to reach the target. Statins are preferred in the reduction of LDL cholesterol, but guidance on their use is not strict.5 If strategy matters, then guidelines should reflect this fact — and performance measures should be changed as well. After all, these measures are intended to hold clinicians accountable for practices whose benefits are widely recognized as far outweighing their risks.
How, then, should guidelines and performance measures change? First, we should no longer support the use of targets without reference to the strategies used to achieve them. Guidelines and performance measures should reflect the evidence about interventions that are known to be beneficial. For example, guidelines for lowering lipid levels should be based on tested strategies and should make it clear that the strategies with the strongest evidence are preferred. A quality measure that incorporated the use of statins into an assessment of lipid-level control would be more scientifically sound than the simple assessment of the proportion of a physician's or practice's patients in whom a specific LDL cholesterol level was reached by any strategy. A quality measure for tight glucose control should require evidence that a proven strategy provides a strong net benefit for patients. We know that we are setting a high standard for developers of performance measures, but advances in our knowledge demand nothing less.
Second, guidelines and performance measures should incorporate more sophisticated and explicit considerations of the risks of disease and adverse consequences posed by the intervention. In patients with a low likelihood of a particular poor outcome, an intervention designed to protect against that outcome is unlikely to provide substantial benefit — so if the intervention carries even a small risk, this risk can offset or even outweigh the benefit. In sicker patients and those with more complex conditions, certain interventions (such as maintenance of tight glucose control) may be more likely to produce adverse effects than they would in healthier patients, either directly or through their effect on adherence. For these patients, we need evidence that the strategy is safe and has a substantial net clinical benefit despite the greater risks of treatment.
The assessment of net clinical benefit should be based on events averted or lives improved. The promulgation of those strategies that are shown to be effective will serve as an incentive for drug and device developers to provide evidence about patient outcomes, not just about how a drug or device affects intermediate outcomes. Moving practice toward evidence-based strategies and becoming more accountable for what we do for patients represent important advances in our delivery of health care, but we must ensure that in implementing quality measures we are always acting in the patient's best interests. ACCORD, ADVANCE, and other recent studies remind us that practice is complex and that ultimately we need to understand a strategy's effects on people, not just on surrogate end points.
No potential conflict of interest relevant to this article was reported.
Source Information
Dr. Krumholz is a professor of medicine at Yale University School of Medicine and director of the Center for Outcomes Research and Evaluation at Yale–New Haven Hospital — both in New Haven, CT. Dr. Lee is network president of Partners HealthCare System in Boston and an associate editor of the Journal. This article (10.1056/NEJMp0803740) was published at www.nejm.org on June 6, 2008. It will appear in the June 12 issue of the Journal.

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