Therapeutic decision making: a cost-benefit analysis
Abstract
To help the physician decide whether or not to treat a patient who may or may not have a disease, a method has been developed for calculating a therapeutic threshold. If the probability of disease in a given patient exceeds the threshold, the preferable course of action is to treat; if the probability is below the threshold, the preferable course of action is to withhold treatment. This method is applicable in many medical and surgical settings in which some diagnostic uncertainty exists after all appropriate studies have been carried out. The technic not only exposes some of the basic principles of therapeutic decision making in the face of diagnostic uncertainty but also forms a convenient framework for analyzing the impact of "soft" clinical data on the decision-making process.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Suggesting advanced surgery to patients who actually have a 10% risk of malignancy based on the ADNEX predictors implies performing advanced surgery in ten individuals per true positive.
“Suggesting advanced surgery to patients who actually have a 10% risk of malignancy based on the ADNEX predictors implies performing advanced surgery in ten individuals per true positive (ie, performing advanced surgery in a patient with a malignant tumour). 18”
From Evaluation of performance measures in predictive artificial intelligence models to support medical decisions: overview and guidance (2025) · cites this paper as [18]
Net benefit sets the decision threshold based on the misclassification costs, following the classic connection between both.
“Net benefit sets the decision threshold based on the misclassification costs, following the classic connection between both.”
From Evaluation of performance measures in predictive artificial intelligence models to support medical decisions: overview and guidance (2025) · cites this paper as [18]
The odds of the risk threshold is the harm-to-benefit ratio, i.e. the ratio of the harm of a false positive and the benefit of a true positive classification.
“The odds of the risk threshold is the harm-to-benefit ratio, i.e. the ratio of the harm of a false positive and the benefit of a true positive classification[21].”
From A calibration hierarchy for risk models was defined: from utopia to empirical data (2016) · cites this paper as [21]
Cites
Decision Analysis: Introductory Lectures on Choices Under Uncertainty.
Klevorick, A. K., & Raiffa, H. (1969) · The Journal of Finance · doi:10.2307/2325714 · Cited by 1,942 · see citing works
ANTICOAGULANT DRUGS IN THE TREATMENT OF PULMONARY EMBOLISM
Barritt, D. W., & Jordan, S. C. (1960) · The Lancet · doi:10.1016/s0140-6736(60)92299-6 · Cited by 1,362 · see citing works
Primer on Certain Elements of Medical Decision Making
McNeil, B. J., Keeler, E., & Adelstein, S. J. (1975) · New England Journal of Medicine · doi:10.1056/nejm197507312930501 · Cited by 1,147 · see citing works
Decision Analysis: Introductory Lectures on Choices Under Uncertainty.
Raiffa, H. (1969) · Journal of the Royal Statistical Society Series D (The Statistician) · doi:10.2307/2987280 · Cited by 947 · see citing works
Decision analysis and clinical judgment
Schwartz, W. B., Gorry, G. A., Kassirer, J. P., & Essig, A. (1973) · The American Journal of Medicine · doi:10.1016/0002-9343(73)90203-9 · Cited by 245 · see citing works
Self-citationJick, H. (1974) · New England Journal of Medicine · doi:10.1056/nejm197410172911605 · Cited by 192 · see citing works
Efficacy of Routine Screening and Lateral Chest Radiographs in a Hospital-Based Population
Sagel, S. S., Evens, R. G., Forrest, J. V., et al. (1974) · New England Journal of Medicine · doi:10.1056/nejm197411072911904 · Cited by 140 · see citing works
The fate of the negative appendix
Chang, F. C., Hogle, H. H., & Welling, D. R. (1973) · The American Journal of Surgery · doi:10.1016/s0002-9610(73)80063-7 · Cited by 136 · see citing works
Treatment of Appendicitis at the Massachusetts General Hospital (1937-1959)
Barnes, B. A. (1962) · JAMA · doi:10.1001/jama.1962.03050150028006 · Cited by 93 · see citing works
DURATION OF ANTICOAGULANT THERAPY IN VENOUS THROMBOEMBOLISM
O'Sullivan, E. F. (1972) · The Medical Journal of Australia · doi:10.5694/j.1326-5377.1972.tb103752.x · Cited by 82 · see citing works
Acute appendicitis—When is it right to be wrong?
Hobson, T., & Rosenman, L. D. (1964) · The American Journal of Surgery · doi:10.1016/0002-9610(64)90024-8 · Cited by 55 · see citing works
THE VALUE OF CONTINUOUS (1 TO 10 YEARS) LONG-TERM ANTICOAGULANT THERAPY
Manchester, B. (1957) · Annals of Internal Medicine · doi:10.7326/0003-4819-47-6-1202 · Cited by 42 · see citing works
Cost-Benefit Analysis of Newborn Screening for Metabolic Disorders
(1974) · New England Journal of Medicine · doi:10.1056/nejm197412262912614 · Cited by 30 · see citing works
Biochemical Screening — A Critique
Ahlvin, R. C. (1970) · New England Journal of Medicine · doi:10.1056/nejm197011122832005 · Cited by 29 · see citing works
Exploratory celiotomy for acute abdominal pain
YAJKO, R. D., & Steele, G. D. (1974) · The American Journal of Surgery · doi:10.1016/0002-9610(74)90068-3 · Cited by 3 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
A calibration hierarchy for risk models was defined: from utopia to empirical data
Van Calster, B., Nieboer, D., Vergouwe, Y., De Cock, B., Pencina, M. J., & Steyerberg, E. W. (2016) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2015.12.005 · Cited by 910 · see citing works
Ozenne, B., Subtil, F., & Maucort-Boulch, D. (2015) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2015.02.010 · Cited by 379 · see citing works
Calibration of Risk Prediction Models: Impact on Decision-Analytic Performance
Van Calster, B., & Vickers, A. J. (2015) · Medical Decision Making · doi:10.1177/0272989x14547233 · Cited by 371 · see citing works
Magruder-Habib, K., Zung, W. W. K., & Feussner, J. R. (1990) · Medical Care · doi:10.1097/00005650-199003000-00004 · Cited by 163 · see citing works
Artificial Intelligence in Medicine
Schwartz, W. B., Patil, R. S., & Szolovits, P. (1987) · New England Journal of Medicine · doi:10.1056/nejm198703123161109 · Cited by 152 · see citing works
Verbakel, J. Y., Steyerberg, E. W., Uno, H., De Cock, B., Wynants, L., Collins, G. S., & Van Calster, B. (2020) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2020.01.028 · Cited by 138 · see citing works
Van Calster, B., Collins, G. S., Vickers, A. J., Wynants, L., Kerr, K. F., Barreñada, L., Varoquaux, G., Singh, K., Moons, K. G., Hernandez-Boussard, T., et al. (2025) · The Lancet Digital Health · doi:10.1016/j.landig.2025.100916 · Cited by 112 · see citing works
Surgeon perception of risk and benefit in the decision to operate.
Sacks, G. D., Dawes, A. J., Ettner, S. L., Brook, R. H., Fox, C. R., Maggard-Gibbons, M., Ko, C. Y., & Russell, M. M. (2016) · Annals of Surgery · doi:10.1097/sla.0000000000001784 · Cited by 100 · see citing works
A spline-based tool to assess and visualize the calibration of multiclass risk predictions
Van Hoorde, K., Van Huffel, S., Timmerman, D., Bourne, T., & Van Calster, B. (2015) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2014.12.016 · Cited by 85 · see citing works
Kuipers, B. (2018) · Communications of the ACM · doi:10.1145/3173087 · Cited by 54 · see citing works
- Authors
- Pauker, S. G., & Kassirer, J. P.
- Affiliations
- Tufts University (US)
- Venue
- New England Journal of Medicine
- Publisher
- Massachusetts Medical Society
- Published
- 1975-07-31
- Volume
- 293
- Issue
- 5
- Pages
- 229-234
- ISSN
- 0028-4793 (ISSN-L)
- 1533-4406
- OpenAlex
- W2041256948
- Cited by
- 507
- References
- 15
- Citations by year
- 2026: 13 · 2025: 15 · 2024: 20 · 2023: 11 · 2022: 12 · 2021: 13 · 2020: 16 · 2019: 13 · 2018: 11 · 2017: 19 · 2016: 15 · 2015: 14 · 2014: 13 · 2013: 15 · 2012: 9
- FWCI
- 11.92
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- New England Journal of Medicine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Family Practice › Clinical Reasoning and Diagnostic Skills
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
- Health Sciences › Health Professions › General Health Professions › Healthcare cost, quality, practices
- Keywords
- treatment decision-making, cost-benefit analysis, treatment thresholds, diagnostic uncertainty, disease probability, withholding treatment, clinical decision-making
- MeSH terms
- Adolescent, Adult, Anticoagulants, Appendicitis, Costs and Cost Analysis, Decision Making, Female, Humans, Male, Models, Theoretical, Probability, Pulmonary Embolism, Statistics as Topic, Therapeutics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
