The median informs the message: accuracy of individualized scenarios for survival time based on oncologists' estimates
Open accessAbstract
Purpose: To determine the accuracy and usefulness of oncologists' estimates of survival time in individual patients with advanced cancer. Patients and Methods: Twenty-one oncologists estimated the “median survival of a group of identical patients” for each of 114 patients with advanced cancer. Accuracy was defined by the proportions of patients with an observed survival time bounded by prespecified multiples of their estimated survival time. We expected 50% to live longer (or shorter) than their oncologist's estimate (calibration), 50% to live from half to double their estimate (typical scenario), 5% to 10% to live ≤ one quarter of their estimate (worst-case scenario), and 5% to 10% to live three or more times their estimate (best-case scenario). Estimates within 0.67 to 1.33 times observed survival were deemed precise. Discriminative value was assessed with Harrell's C-statistic and prognostic significance with proportional hazards regression. Results: Median survival time was 11 months. Oncologists' estimates were relatively well-calibrated (61% shorter than observed), imprecise (29% from 0.67 to 1.33 times observed), and moderately discriminative (Harrell C-statistic 0.63; P = .001). The proportion of patients with an observed survival half to double their oncologist's estimate was 63%, ≤ one quarter of their oncologist's estimate was 6%, and three or more times their oncologist's estimate was 14%. Independent predictors of observed survival were oncologist's estimate (hazard ratio [HR] = 0.92; P = .004), dry mouth (HR = 5.1; P < .0001), alkaline phosphatase more than 101U/L (HR = 2.8; P = .0002), Karnofsky performance status ≤ 70 (HR = 2.3; P = .007), prostate primary (HR = 0.23; P = .002), and steroid use (HR = 2.4; P = .02). Conclusion: Oncologists' estimates of survival time were relatively well-calibrated, moderately discriminative, independently associated with observed survival, and a reasonable basis for estimating worst-case, typical, and best-case scenarios for survival.
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Survival ranges are more accurate than a single expected survival estimate.
“Ranges for survival scenarios are also more accurate than a single point estimate of expected survival.16 , 32 , 33”
From 5th ESO-ESMO international consensus guidelines for advanced breast cancer (ABC 5) (2020) · cites this paper as [33]
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References 34 · Cited by 62
- Authors
- Kiely, B. E., Martin, A. J., Tattersall, M. H. N., Nowak, A. K., Goldstein, D., Wilcken, N. R. C., Wyld, D. K., Abdi, E. A., Glasgow, A., Beale, P. J., Jefford, M., Glare, P. A., & Stockler, M. R.
- Affiliations
- The University of Sydney (AU)
- ORCID
- Venue
- Journal of Clinical Oncology
- Published
- 2013-10-01
- Volume
- 31
- Issue
- 28
- Pages
- 3565-3571
- ISSN
- 0732-183X (ISSN-L)
- 1527-7755
- OpenAlex
- W2135995108
- Cited by
- 62
- References
- 34
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 8 · 2023: 2 · 2022: 2 · 2021: 3 · 2020: 13 · 2019: 9 · 2018: 3 · 2017: 3 · 2016: 7 · 2015: 6 · 2014: 2
- FWCI
- 5.10
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Clinical Oncology (publishedVersion)
- PubMed (publishedVersion)
- UWA Profiles and Research Repository (UWA) (submittedVersion)
- Funders
- Pfizer
- Pfizer Australia
- National Breast Cancer Foundation
- Cancer Institute NSW
- Medical Research Council
- National Health and Medical Research Council
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Palliative Care and End-of-Life Issues
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Palliative and Oncologic Care
- Keywords
- survival time estimation, advanced cancer, prognostic discrimination, prognostic factors, xerostomia, alkaline phosphatase, Karnofsky performance status, prostate cancer, steroid use
- MeSH terms
- Aged, Female, Follow-Up Studies, Humans, Life Expectancy, Male, Medical Oncology, Middle Aged, Mortality, Neoplasms, Physician's Role, Prognosis, Prospective Studies, Time Factors, Survival Rate, Karnofsky Performance Status
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