Evidence map›Paper›PMID 32422506›Full record

ArticleEuropean journal of cancer (Oxford, England : 1990)2020

Precision oncology: the intention-to-treat analysis fallacy.

Jason K Sicklick, Shumei Kato, Ryosuke Okamura, Razelle Kurzrock

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in European journal of cancer (Oxford, England : 1990), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 44% of its field
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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Jason K SicklickDivision of Surgical Oncology, Department of Surgery, University of California, San Diego, La Jolla, CA, USA; Moores Cancer Center, University of California, San Diego, La Jolla, CA, USA; Center for Personalized Cancer Therapy, University of California, San Diego, La Jolla, CA, USA. Electronic address: jsicklick@health.ucsd.edu.
Shumei KatoMoores Cancer Center, University of California, San Diego, La Jolla, CA, USA; Center for Personalized Cancer Therapy, University of California, San Diego, La Jolla, CA, USA; Division of Hematology Oncology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA.
Ryosuke OkamuraMoores Cancer Center, University of California, San Diego, La Jolla, CA, USA; Center for Personalized Cancer Therapy, University of California, San Diego, La Jolla, CA, USA; Division of Hematology Oncology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA.
Razelle KurzrockMoores Cancer Center, University of California, San Diego, La Jolla, CA, USA; Center for Personalized Cancer Therapy, University of California, San Diego, La Jolla, CA, USA; Division of Hematology Oncology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA. Electronic address: rkurzrock@health.ucsd.edu.
University of California San Diego · US

Funding

VIRAL MALIGNANCYP30CA023100 · NCI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Jesse Nodora · 1985 to 2026
$124.9M
Targeting Drug-Resistant Cancer Stem Cell Niches of Gastrointestinal Stromal TumorR01CA226803 · NCI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SICKLICK, JASON KEITH · 2019 to 2023
$2.1M
Investigation of DNA Damaging Agents in GIST with Metabolic DysfunctionR01FD006334 · FDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SICKLICK, JASON KEITH · 2019 to 2021
$1.5M
Novel Allosteric Kinase Inhibitors Target Imatinib-Resistant GISTK08CA168999 · NCI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SICKLICK, JASON KEITH · 2014 to 2018
$888k
Defining the Germline Genomic Landscape of a Novel GIST Multi-tumor SyndromeR21CA192072 · NCI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SICKLICK, JASON KEITH · 2016 to 2017
$399k
FDA HHS R01 FD006334NCI NIH HHS K08 CA168999NCI NIH HHS P30 CA023100NCI NIH HHS R01 CA226803NCI NIH HHS R21 CA192072
6 · The paper itself

Abstract

It has recently been suggested that precision oncology studies should be reanalysed using the intention-to-treat (ITT) methodology developed for randomized controlled clinical trials. This reanalysis dramatically decreases response rates in precision medicine studies. We contend that the ITT analysis of precision oncology trials is invalid. The ITT methodology was developed three decades ago to mitigate the problems of randomized trials, which try to ensure that both arms have an unselected patient population free from confounders. In contrast, precision oncology trials specifically select patients for confounders (that is biomarkers) that predict response. To demonstrate the issues inherent in an ITT reanalysis for precision cancer medicine studies, we take as an example the drug larotrectinib (TRK inhibitor) approved because of remarkable responses in malignancies harbouring NTRK fusions. Based on large-scale studies, NTRK fusions are found in ~0.31% of tumours. In a non-randomized pivotal study of larotrectinib, 75% of the 55 treated patients responded. Based upon the prevalence of NTRK fusions, ~18,000 patients would need to be screened to enrol the 55 treated patients. Utilizing the ITT methodology, the revised response rate to larotrectinib would be 0.23%. This is, of course, a dramatic underestimation of the efficacy of this now Food and Drug Administration (FDA)-approved drug. Similar issues can be shown for virtually any biomarker-based precision clinical trial. Therefore, retrofitting the ITT analysis developed for unselected patient populations in randomized trials yields misleading conclusions in precision medicine studies.

Indexed as

Intention to Treat AnalysisMedical OncologyPrecision MedicineBiasFalse Positive ReactionsHumansMolecular Targeted TherapyNeoplasmsProtein Kinase InhibitorsRandomized Controlled Trials as TopicResearch DesignTreatment OutcomeProtein Kinase InhibitorsIntention-to-treatPrecision oncology

Identifiers

PMID32422506
PMCPMC7786388
OpenAlexW3025822327

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.