ArticleMedical decision making : an international journal of the Society for Medical Decision Making2017
Biases in Individualized Cost-effectiveness Analysis: Influence of Choices in Modeling Short-Term, Trial-Based, Mortality Risk Reduction and Post-Trial Life Expectancy.
Article in Medical decision making : an international journal of the Society for Medical Decision Making, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 5 citations in OpenAlex.
- An economic evaluation of a primary care-based technology-enabled intervention for stroke secondary prevention and management in rural China: a study protocol.Frontiers in neurology · 2023Article
- Targeting of the diabetes prevention program leads to substantial benefits when capacity is constrained.Acta diabetologica · 2021Article
- Risk-Targeted Lung Cancer Screening: A Cost-Effectiveness Analysis.Annals of internal medicine · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundThe benefits and costs of a treatment are typically heterogeneous across individual patients. Randomized clinical trials permit the examination of individualized treatment benefits over the trial horizon but extrapolation to lifetime horizon usually involves combining trial-based individualized estimates of short-term risk reduction with less detailed (less granular) population life tables. However, the underlying assumption of equal post-trial life expectancy for low- and high-risk patients of the same sex and age is unrealistic. We aimed to study the influence of unequal granularity between models of short-term risk reduction and life expectancy on individualized estimates of cost-effectiveness of aggressive thrombolysis for patients with an acute myocardial infarction.
methodsTo estimate life years gained, we multiplied individualized estimates of short-term risk reduction either with less granular and with equally granular post-trial life expectancy estimates. Estimates of short-term risk reduction were obtained from GUSTO trial data (30,510 patients) using logistic regression analysis with treatment, sex, and age as predictor variables. Life expectancy estimates were derived from sex- and age-specific US life tables.
resultsBased on sex- and age-specific, short-term risk reductions but average population life expectancy (less granularity), we found that aggressive thrombolysis was cost-effective (incremental cost-effectiveness ratio below $50,000) for women above age 49 y and men above age 53 y (92% and 69% of the population, respectively). Considering sex- and age-specific short-term mortality risk reduction and correspondingly sex- and age-specific life expectancy (equal granularity), aggressive thrombolysis was cost-effective for men above age 45 y and women above age 50 y (95% and 76% of the population, respectively).
conclusionsFailure to model short-term risk reduction and life expectancy at an equal level of granularity may bias our estimates of individualized cost-effectiveness and misallocate resources.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.