Evidence map›Paper›PMID 39234243›Full record

ReviewFrontiers in immunology2024

An overview of statistical methods for biomarkers relevant to early clinical development of cancer immunotherapies.

David Dejardin, Anton Kraxner, Emilie Schindler, Nicolas Städler, Marcel Wolbers

Abstract readReview
In one paragraph

Review in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  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

5 authors.

David Dejardin *Data Sciences, Product Development, F. Hoffmann-La Roche AG, Basel, Switzerland.
Anton Kraxner *Roche Pharma Research and Early Development Oncology, F. Hoffmann-La Roche AG, Basel, Switzerland.
Emilie Schindler *Roche Pharma Research and Early Development Oncology, F. Hoffmann-La Roche AG, Basel, Switzerland.
Nicolas Städler *Roche Pharma Research and Early Development Oncology, F. Hoffmann-La Roche AG, Basel, Switzerland.
Marcel Wolbers *Data Sciences, Product Development, F. Hoffmann-La Roche AG, Basel, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the last decade, a new paradigm for cancer therapies has emerged which leverages the immune system to act against the tumor. The novel mechanism of action of these immunotherapies has also introduced new challenges to drug development. Biomarkers play a key role in several areas of early clinical development of immunotherapies including the demonstration of mechanism of action, dose finding and dose optimization, mitigation and prevention of adverse reactions, and patient enrichment and indication prioritization. We discuss statistical principles and methods for establishing the prognostic, predictive aspect of a (set of) biomarker and for linking the change in biomarkers to clinical efficacy in the context of early development studies. The methods discussed are meant to avoid bias and produce robust and reproducible conclusions. This review is targeted to drug developers and data scientists interested in the strategic usage and analysis of biomarkers in the context of immunotherapies.

Indexed as

Biomarkers, TumorBiostatisticsImmunotherapyNeoplasmsHumansPrognosisBiomarkers, Tumorbiomarkersimmunotherapypredictive modelprognostic modelstatistical methodsvalidation

Identifiers

PMID39234243
PMCPMC11371698

What OpenQuestion holds

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Registered trials

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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.