Evidence map›Paper›PMID 26914340›Full record

SynthesisJAMA oncology2016

Response Rate as a Regulatory End Point in Single-Arm Studies of Advanced Solid Tumors.

Geoffrey R Oxnard, Katharine H Wilcox, Mithat Gonen, Mikhael Polotsky, Bradford R Hirsch, Lawrence H Schwartz

Abstract readMeta-Analysis
In one paragraph

Synthesis in JAMA oncology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 6 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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  17. Targeted Therapies, Novel Antibodies, and Immunotherapies in Advanced Non-Small Cell Lung Cancer: Clinical Evidence and Drug Approval Patterns.Clinical cancer research : an official journal of the American Association for Cancer Research · 2024
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Geoffrey R OxnardLowe Center for Thoracic Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.
Katharine H WilcoxLowe Center for Thoracic Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.
Mithat GonenDepartment of Biostatistics and Epidemiology, Memorial Sloan Kettering Cancer Center, New York.
Mikhael PolotskyDepartment of Radiology, Columbia University College of Physicians and Surgeons and New York Presbyterian Hospital, New York.
Bradford R HirschDuke Cancer Care Research Program, Duke Cancer Institute, Dallas, Texas.
Lawrence H SchwartzDepartment of Radiology, Columbia University College of Physicians and Surgeons and New York Presbyterian Hospital, New York.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
Quantitative Volume and Density Response Assessment: Sarcoma and HCC as a ModelU01CA140207 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SCHWARTZ, LAWRENCE H, ZHAO, BINSHENG · 2011 to 2015
$2.8M
NCI NIH HHS P30 CA008748NCI NIH HHS U01 CA140207
6 · The paper itself

Abstract

importanceObjective response rate (ORR) is an increasingly important end point for accelerated development of highly active anticancer therapies, yet its relationship to regulatory approval is not well characterized.

objectiveTo identify circumstances in which a high ORR is associated with regulatory approval, and therefore might be an appropriate end point for definitive single-arm studies of anticancer therapies. DATA SOURCE: A database of all oncology clinical trials registered at clinicaltrials.gov between October 1, 2007, and September 30, 2010. STUDY SELECTION: Trials of palliative systemic therapies for 4 measurable solid tumor types, limited to those with trial arms of at least 20 patients reporting ORR per Response Evaluation Criteria in Solid Tumors (RECIST). DATA EXTRACTION AND SYNTHESIS: A systematic search was used to identify the reported ORR for each eligible treatment arm that had been presented publicly. MAIN OUTCOMES AND MEASURES: For each treatment regimen, defined as a single-agent or unique combination of agents for 1 cancer type, the mean ORR and the maximum ORR statistically exceeded were calculated, and their association with regulatory approval was studied. A regimen was considered approved for a specific cancer type if it had received regulatory approval in any country for treatment of advanced cancer of that type.

resultsFrom 1800 trials, 874 eligible trial arms in 578 eligible trials were identified; 542 arms had ORR data available for 294 regimens. Maximum ORR and mean ORR were significantly associated with regulatory approval (τ = 0.27, P < .001; τ = 0.12, P = .01); this relationship was stronger for single-agent therapies (τ = 0.49; τ = 0.41) than for combination regimens (τ = 0.28; τ = 0.17). Evaluation of ORR thresholds between 20% and 60% as potential trial end points demonstrated that ORR statistically exceeding 30% with a single agent had 98% specificity and 89% positive predictive value for identifying regimens achieving regulatory approval. CONCLUSIONS AND RELEVANCE: For single-agent regimens, high ORR was associated with regulatory approval; this relationship was less strong for combination regimens. Our data suggest that high ORR (eg, statistically exceeding an ORR of 30%) is an appropriate end point for single-arm trials aiming to demonstrate breakthrough activity of a single-agent anticancer therapy.

Indexed as

Endpoint DeterminationAntineoplastic AgentsClinical Trials as TopicHumansNeoplasmsAntineoplastic Agents

Identifiers

PMID26914340
PMCPMC5574183

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.