Dataset Information

Can Oncologists Predict the Efficacy of Treatments in Randomized Trials?

ABSTRACT:

Background

Decisions about trial funding, ethical approval, or clinical practice guideline recommendations require expert judgments about the potential efficacy of new treatments. We tested whether individual and aggregated expert opinion of oncologists could predict reliably the efficacy of cancer treatments tested in randomized controlled trials.

Materials and methods

An international sample of 137 oncologists specializing in genitourinary, lung, and colorectal cancer provided forecasts on primary outcome attainment for five active randomized cancer trials within their subspecialty; skill was assessed using Brier scores (BS), which measure the average squared deviation between forecasts and outcomes.

Results

A total of 40% of trials in our sample reported positive primary outcomes. Experts generally anticipated this overall frequency (mean forecast, 34%). Individual experts on average outperformed random predictions (mean BS = 0.29 [95% confidence interval (CI), 0.28-0.33] vs. 0.33) but underperformed prediction algorithms that always guessed 50% (BS = 0.25) or that were trained on base rates (BS = 0.19). Aggregating forecasts improved accuracy (BS = 0.25; 95% CI, 0.16-0.36]). Neither individual experts nor aggregated predictions showed appreciable discrimination between positive and nonpositive trials (area under the curve of a receiver operating characteristic curve, 0.52 and 0.43, respectively).

Conclusion

These findings are based on a limited sample of trials. However, they reinforce the importance of basing research and policy decisions on the results of randomized trials rather than expert opinion or low-level evidence.

Implications for practice

Predictions of oncologists, either individually or in the aggregate, did not anticipate reliably outcomes for randomized trials in cancer. These findings suggest that pooled expert opinion about treatment efficacy is no substitute for randomized trials. They also underscore the challenges of using expert opinion to prioritize interventions for clinical trials or to make recommendations in clinical practice guidelines.

SUBMITTER: Benjamin DM

PROVIDER: S-EPMC7794184 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Publications

Can Oncologists Predict the Efficacy of Treatments in Randomized Trials?

Benjamin Daniel M DM Mandel David R DR Barnes Tristan T Krzyzanowska Monika K MK Leighl Natasha N Tannock Ian F IF Kimmelman Jonathan J

The oncologist 20200826 1

<h4>Background</h4>Decisions about trial funding, ethical approval, or clinical practice guideline recommendations require expert judgments about the potential efficacy of new treatments. We tested whether individual and aggregated expert opinion of oncologists could predict reliably the efficacy of cancer treatments tested in randomized controlled trials.<h4>Materials and methods</h4>An international sample of 137 oncologists specializing in genitourinary, lung, and colorectal cancer provided f ...[more]

PMID: 32936509

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Dataset Information

Can Oncologists Predict the Efficacy of Treatments in Randomized Trials?

Background

Materials and methods

Results

Conclusion

Implications for practice

Publications

Can Oncologists Predict the Efficacy of Treatments in Randomized Trials?

Similar Datasets

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