Evidence map›Paper›PMID 36383380›Full record

ArticleJAMA network open2022

Characterization of Oncology Clinical Trials Using Germline Genetic Data.

Ashwin V Kammula, Alejandro A Schäffer, Padma Sheila Rajagopal

Open access · goldAbstract read
In one paragraph

Article in JAMA network open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 35% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Targeted therapy in patients with genetic tumor syndromes.Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V · 2025
    Article
  5. Article
  6. Article
  7. Universal Germline and Tumor Genomic Testing Needed to Win the War Against Cancer:Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2023
    Article
  8. 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

3 authors at 1 institution in 1 country.

Ashwin V KammulaCancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland.
Alejandro A SchäfferCancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland.
Padma Sheila RajagopalCancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland.
Center for Cancer Research · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: The recent successes of poly-ADP ribose polymerase (PARP) inhibitors and belzutifan support germline genetic data as an exciting, accessible source for biomarkers in cancer treatment. This study hypothesizes, however, that most oncology clinical trials using germline data largely prioritize BRCA1/2 as biomarkers and PARP inhibitors as therapy. Objective: To characterize past and ongoing oncology trials that use germline data. Design, Setting, and Participants: This retrospective cross-sectional study of oncology trials used the Informa Trialtrove database to evaluate trial attributes. Trials using germline information (including the terms germline, hereditary, or inherited in the title, treatment plan, interventions, end points, objectives, results, or notes) and conducted globally between December 1, 1990, and April 4, 2022 (data freeze date), were included. Main Outcomes and Measures: Trials by cancer type, phase, participants, sponsor type, end points, outcomes, and locations were described. Associated biomarkers and mechanisms of action for studied therapeutic interventions were counted. How germline data in trial inclusion and exclusion criteria are associated with end points, outcomes, and enrollment were also examined. Results: A total of 887 of 84 297 (1.1%) oncology clinical trials in the Trialtrove database that use germline data were identified. Most trials were conducted in cancer types where PARP inhibitors are already approved. A total of 74.8% (672) of trials were performed in the phase 2 setting or above. Trials were primarily sponsored by industry (523 trials [59.0%]), academia (382 trials [43.1%]), and the government (274 trials [30.9%]), where trials may have multiple sponsor types. Among 343 trials using germline data with outcomes in Trialtrove, 180 (52.5%) reported meeting primary end points. Although BRCA1/2 are the most frequent biomarkers seen (BRCA1, 224 trials [25.3%]; BRCA2, 228 trials [25.7%]), trials also examine pharmacogenomic variants and germline mediators of somatic biomarkers. PARP inhibitors or immunotherapy were tested in 69.9% of trials; PARP inhibition was the most frequently studied mechanism (367 trials [41.4%]). An overwhelming number of trials using germline data were conducted in the US, Canada, and Europe vs other countries, mirroring disparities in cancer genetics data. Germline data in inclusion and exclusion criteria are associated with altered end point, outcomes, and enrollment compared with oncology trials with no germline data use. Examples of inclusion and exclusion criteria regarding germline data that may unintentionally exclude patients were identified. Conclusions and Relevance: These findings suggest that for germline biomarkers to gain clinical relevance, trials must expand biomarkers, therapies, and populations under study.

Indexed as

NeoplasmsPoly(ADP-ribose) Polymerase InhibitorsBiomarkersClinical Trials as TopicCross-Sectional StudiesHumansRetrospective StudiesBiomarkersPoly(ADP-ribose) Polymerase Inhibitors

Identifiers

PMID36383380
PMCPMC9669814
OpenAlexW4309350451

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.