Using Evidence to Combat Overdiagnosis and Overtreatment: Evaluating Treatments, Tests, and Disease Definitions in the Time of Too Much

English: A Collection of Articles on Disease M...
English: A Collection of Articles on Disease Mongering in PLoS Medicine Español: Portada del monográfico publicado en Public Library of Science – Medicine sobre promoción de enfermedades (Photo credit: Wikipedia)


PLOS Medicine. 

  • Ray Moynihan

As a matter of urgency, the potential for overdiagnosis and related overtreatment should be routinely considered for inclusion in the introduction and discussion sections of reports of studies of therapies, studies of diagnostic test accuracy, systematic reviews of those studies, clinical guidelines, and changes to disease definitions (Box 1). Second, there is a clear need for more research—both original studies and reviews of studies—into the nature and extent of overdiagnosis and related overtreatment within specific conditions—as, for example, has occurred with studies on the risks associated with mammography [5]. Third, the potential harms associated with new treatments and tests, or expanded disease definitions, demand much greater attention in primary studies and reviews.

Box 1. Summary of Suggestions for Improving the Evidence Base to Combat Overdiagnosis and Related Overtreatment

  1. Routine consideration of overdiagnosis and related overtreatment in the introduction and discussion sections of primary studies and systematic review articles about tests and treatments
  2. More condition-specific studies and reviews on the risk of overdiagnosis and related overtreatment—e.g., diagnosis of pulmonary embolism
  3. More rigorous routine evaluation of potential harms of treatments, tests, and changes to disease definitions
  4. In studies and reviews of studies of therapies, clearer stratification by baseline risk, to better identify treatment thresholds where benefits are likely to outweigh harms
  5. In studies and reviews of studies of test accuracy, more clarity about which target condition or spectrum of a disease is being considered, with a shift from a dichotomous “disease/no disease” frame to a “spectrum of disease severity” frame, and a linking of test accuracy to consequences for treatment and patient outcomes
  6. Panels that review and change disease definitions that are free of conflicts, and routinely consider evidence for potential harms as well as potential benefits of the changes they propose

For evaluation of treatments, more clarity is required about the specific definitions of diseases being treated in primary treatment studies and subsequent systematic reviews. As per the recommendations of Kent and colleagues [11], clearer stratification of groups at varying degrees of baseline risk or disease stage is needed, to better identify treatment thresholds at which the harms of treatment start to outweigh benefits. Sometimes this will require re-analysis of large (e.g., pooled individual participant) datasets, underscoring the need for access to raw data from trials.

For primary studies and reviews of studies of diagnostic test accuracy, there is a need to make explicit exactly which stages or spectrum of a target disease is being considered—also referred to as the “target condition” [14]. Where possible, it may be desirable to shift the paradigm from a dichotomous frame—disease presence versus absence—to thinking about a spectrum of disease severity. Moreover, when diagnostic studies show improved detection (or exclusion) of specific disease stages, researchers should try to link the consequences of such improved diagnostic accuracy to subsequent treatment decisions. Ideally, the consequences of such changed treatment decisions for patient outcomes might also be addressed [16]. Such elaborations to conventional diagnostic test accuracy studies would help identify at what diagnostic disease spectrum thresholds subsequent treatments will do more good than harm.

And, finally, the need to improve the process of disease definition—with awareness of the dangers of overdiagnosis and overtreatment—is being increasingly accepted, with international organisations, including the Guidelines International Network, currently looking to develop new guidance. While a detailed debate will ensue in coming years, we believe several key principles might underpin the reform of how disease definitions are changed: panel members should be free of financial and reputational conflicts of interest; strong evidence, ideally from randomised trial data, should demonstrate that the use of new criteria will meaningfully reduce mortality and/or morbidity; and potential benefits and potential harms of labelling and treatment using the new criteria should be explicitly investigated and reported.


We offer these suggestions as part of the wider scientific debate underway on how to safely and fairly wind back the harms of too much medicine [17]. We are hopeful that a heightened attention to the dangers of overdiagnosis and related overtreatment may lead to an enhanced evidence base on these topics. This, in turn, will help produce fairer, more rational, and less wasteful health care systems, built on a reformed process of disease definition that offers diagnostic labels and medical interventions only to those likely to benefit from them.

BMJ: How to read a paper

Education and debate

Papers that go beyond numbers (qualitative research)

Trisha Greenhalgh, Rod Taylor Papers that summarise other papers (systematic reviews and meta-analyses)

Trisha Greenhalgh

Papers that tell you what things cost (economic analyses)

Trisha Greenhalgh

Papers that report diagnostic or screening tests

Trisha Greenhalgh

Papers that report drug trials

Trisha Greenhalgh

Statistics for the non-statistician. II: “Significant” relations and their pitfalls

Trisha Greenhalgh

Statistics for the non-statistician

Trisha Greenhalgh

Assessing the methodological quality of published papers

Trisha Greenhalgh

Getting your bearings (deciding what the paper is about)

Trisha Greenhalgh

The Medline database

Trisha Greenhalgh

If you would like to order a copy of this book, please visit the BMJ Publishing Group website (under Medical Journalism/Research)

English: Histogram of sepal widths for Iris ve...
English: Histogram of sepal widths for Iris versicolor from Fisher’s Iris flower data set. SVG redraw of original image. (Photo credit: Wikipedia)

Biblioteca Virtual: Family Medicine

Otro regalo de fin de año: gracias Rochy alli en Arizona.

Product Details
»Book Publisher: McGraw-Hill Medical (01 November, 2004)
»ISBN: 0071423222
»Book author: Mark B. Mengel, L. Peter Schwiebert
»Amazon Rating: 5.0Book Description:
A quick reference guide to the diagnosis and treatment of common primary care problems. The information is presented in such a way as to help students and physicians quickly form a list of possible diagnoses, perform a cost-effective diagnostic work-up, and prescribe therapy for the most common causes of acute and chronic complaints. Principles of clinical decision making and efficient management strategies are integrated throughout the book.
Gracias Rochy 🙂