Evidence map›Paper›PMID 26503199›Full record

Trial reportJournal of clinical oncology : official journal of the American Society of Clinical Oncology2015

Clinical Utility of Metrics Based on Tumor Measurements in Phase II Trials to Predict Overall Survival Outcomes in Phase III Trials by Using Resampling Methods.

Ming-Wen An, Yu Han, Jeffrey P Meyers, Jan Bogaerts, Daniel J Sargent, Sumithra J Mandrekar

Abstract readClinical Trial, Phase IIClinical Trial, Phase IIIMulticenter Study
In one paragraph

Trial report in Journal of clinical oncology : official journal of the American Society of Clinical Oncology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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

6 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
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.

Ming-Wen AnMing-Wen An, Vassar College, Poughkeepsie, NY; Yu Han, Novartis Pharmaceuticals, East Hanover NJ; Jeffrey Meyers, Daniel J. Sargent, and Sumithra J. Mandrekar, Mayo Clinic, Rochester, MN; and Jan Bogaerts, European Organisation for Research and Treatment of Cancer, Brussels, Belgium. mian@vassar.edu.
Yu HanMing-Wen An, Vassar College, Poughkeepsie, NY; Yu Han, Novartis Pharmaceuticals, East Hanover NJ; Jeffrey Meyers, Daniel J. Sargent, and Sumithra J. Mandrekar, Mayo Clinic, Rochester, MN; and Jan Bogaerts, European Organisation for Research and Treatment of Cancer, Brussels, Belgium.
Jeffrey P MeyersMing-Wen An, Vassar College, Poughkeepsie, NY; Yu Han, Novartis Pharmaceuticals, East Hanover NJ; Jeffrey Meyers, Daniel J. Sargent, and Sumithra J. Mandrekar, Mayo Clinic, Rochester, MN; and Jan Bogaerts, European Organisation for Research and Treatment of Cancer, Brussels, Belgium.
Jan BogaertsMing-Wen An, Vassar College, Poughkeepsie, NY; Yu Han, Novartis Pharmaceuticals, East Hanover NJ; Jeffrey Meyers, Daniel J. Sargent, and Sumithra J. Mandrekar, Mayo Clinic, Rochester, MN; and Jan Bogaerts, European Organisation for Research and Treatment of Cancer, Brussels, Belgium.
Daniel J SargentMing-Wen An, Vassar College, Poughkeepsie, NY; Yu Han, Novartis Pharmaceuticals, East Hanover NJ; Jeffrey Meyers, Daniel J. Sargent, and Sumithra J. Mandrekar, Mayo Clinic, Rochester, MN; and Jan Bogaerts, European Organisation for Research and Treatment of Cancer, Brussels, Belgium.
Sumithra J MandrekarMing-Wen An, Vassar College, Poughkeepsie, NY; Yu Han, Novartis Pharmaceuticals, East Hanover NJ; Jeffrey Meyers, Daniel J. Sargent, and Sumithra J. Mandrekar, Mayo Clinic, Rochester, MN; and Jan Bogaerts, European Organisation for Research and Treatment of Cancer, Brussels, Belgium.

Funding

Member Site CoreU10CA180821 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI Evanthia Galanis · 2014 to 2026
$177.3M
Women's Cancer ProgramP30CA015083 · NCI · MAYO CLINIC ROCHESTER · PI Felicity Enders · 1985 to 2026
$151.3M
Statistics CoreU10CA180882 · NCI · MAYO CLINIC ROCHESTER · PI Sumithra Jay Mandrekar · 2014 to 2026
$115.0M
Validation of New Tumor Measurement-based Phase II Clinical Trial EndpointsR21CA167326 · NCI · MAYO CLINIC ROCHESTER · PI AN, MING-WEN, MANDREKAR, SUMITHRA JAY · 2012 to 2013
$373k
NCI NIH HHS CA167326NCI NIH HHS P30 CA015083NCI NIH HHS R21 CA167326NCI NIH HHS U10 CA180821NCI NIH HHS U10 CA180882
6 · The paper itself

Abstract

purposePhase II clinical trials inform go/no-go decisions for proceeding to phase III trials, and appropriate end points in phase II trials are critical for facilitating this decision. Phase II solid tumor trials have traditionally used end points such as tumor response defined by Response Evaluation Criteria for Solid Tumors (RECIST). We previously reported that absolute and relative changes in tumor measurements demonstrated potential, but not convincing, improvement over RECIST to predict overall survival (OS). We have evaluated the metrics by using additional measures of clinical utility and data from phase III trials.

methodsResampling methods were used to assess the clinical utility of metrics to predict phase III outcomes from simulated phase II trials. In all, 2,000 phase II trials were simulated from four actual phase III trials (two positive for OS and two negative for OS). Cox models for three metrics landmarked at 12 weeks and adjusted for baseline tumor burden were fit for each phase II trial: absolute changes, relative changes, and RECIST. Clinical utility was assessed by positive predictive value and negative predictive value, that is, the probability of a positive or negative phase II trial predicting an effective or ineffective phase III conclusion, by prediction error, and by concordance index (c-index).

resultsAbsolute and relative change metrics had higher positive predictive value and negative predictive value than RECIST in five of six treatment comparisons and lower prediction error curves in all six. However, differences were negligible. No statistically significant difference in c-index across metrics was found.

conclusionThe absolute and relative change metrics are not meaningfully better than RECIST in predicting OS.

Indexed as

Decision Support Systems, ClinicalModels, StatisticalTumor BurdenCarcinoma, Non-Small-Cell LungCohort StudiesColorectal NeoplasmsDisease ProgressionFollow-Up StudiesHumansLung NeoplasmsNeoplasm StagingPredictive Value of TestsPrognosisProportional Hazards ModelsSurvival Rate

Identifiers

PMID26503199
PMCPMC4669590

What OpenQuestion holds

Textmetadata
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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.