Does biomarker use in oncology improve clinical trial failure risk? A large-scale analysis.
Antineoplastic Agents
/ therapeutic use
Biomarkers, Tumor
/ classification
Breast Neoplasms
/ chemistry
Carcinoma, Non-Small-Cell Lung
/ chemistry
Clinical Trials as Topic
/ classification
Clinical Trials, Phase I as Topic
Clinical Trials, Phase II as Topic
Clinical Trials, Phase III as Topic
Colorectal Neoplasms
/ chemistry
Databases, Factual
/ statistics & numerical data
Drug Approval
/ methods
Female
Genetic Markers
Humans
Lung Neoplasms
/ chemistry
Male
Markov Chains
Medical Oncology
Melanoma
/ chemistry
Neoplasms
/ chemistry
Risk
Skin Neoplasms
/ chemistry
Stochastic Processes
Time Factors
Treatment Failure
biomarkers
breast cancer
cancer
clinical trial
drug development
lung cancer
melanoma
oncology
risk
Journal
Cancer medicine
ISSN: 2045-7634
Titre abrégé: Cancer Med
Pays: United States
ID NLM: 101595310
Informations de publication
Date de publication:
03 2021
03 2021
Historique:
revised:
25
11
2020
received:
12
01
2020
accepted:
01
12
2020
pubmed:
24
2
2021
medline:
20
7
2021
entrez:
23
2
2021
Statut:
ppublish
Résumé
To date there has not been an extensive analysis of the outcomes of biomarker use in oncology. Data were pooled across four indications in oncology drawing upon trial outcomes from www.clinicaltrials.gov: breast cancer, non-small cell lung cancer (NSCLC), melanoma and colorectal cancer from 1998 to 2017. We compared the likelihood drugs would progress through the stages of clinical trial testing to approval based on biomarker status. This was done with multi-state Markov models, tools that describe the stochastic process in which subjects move among a finite number of states. Over 10000 trials were screened, which yielded 745 drugs. The inclusion of biomarker status as a covariate significantly improved the fit of the Markov model in describing the drug trajectories through clinical trial testing stages. Hazard ratios based on the Markov models revealed the likelihood of drug approval with biomarkers having nearly a fivefold increase for all indications combined. A 12, 8 and 7-fold hazard ratio was observed for breast cancer, melanoma and NSCLC, respectively. Markov models with exploratory biomarkers outperformed Markov models with no biomarkers. This is the first systematic statistical evidence that biomarkers clearly increase clinical trial success rates in three different indications in oncology. Also, exploratory biomarkers, long before they are properly validated, appear to improve success rates in oncology. This supports early and aggressive adoption of biomarkers in oncology clinical trials.
Identifiants
pubmed: 33620160
doi: 10.1002/cam4.3732
pmc: PMC7957156
doi:
Substances chimiques
Antineoplastic Agents
0
Biomarkers, Tumor
0
Genetic Markers
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1955-1963Informations de copyright
© 2021 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.
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