Evidence map›Paper›PMID 40762767›Full record

ArticleTherapeutic innovation & regulatory science2025

Ensuring Quality and Interpretability of Progression Free Survival and Overall Survival in Oncology Clinical Trials.

Philip He, Haijun Ma, Chengxing Cindy Lu, Revathi Ananthakrishnan, Gu Mi, Thomas Gwise, Laura Fernandes, Hui Yang, David Leung, Natalie Ren and 1 more

Abstract read
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In one paragraph

Article in Therapeutic innovation & regulatory science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

11 authors.

Philip HeBiostatistics,Daiichi Sankyo Inc., 211 Mt Airy Rd, Basking Ridge, New Jersey, USA. philipyihe2018@gmail.com.
Haijun MaBiostatistics, Exelixis, CA, USA.
Chengxing Cindy LuOncology Biometrics, AstraZeneca, MA, USA.
Revathi AnanthakrishnanGlobal Biometrics and Data Sciences, Bristol-Myers Squibb, NJ, USA.
Gu MiEvidence Generation and Decision Science, Sanofi, MA, USA.
Thomas GwiseT Gwise Consulting LLC, FL, USA.
Laura FernandesBiostatistics, COTA Healthcare Inc., MD, USA.
Hui YangStatistical & Quantitative Sciences, Takeda, MA, USA.
David LeungClinical Development, Daiichi Sankyo Inc., NJ, USA.
Natalie RenClinical Science, iTeos Therapeutics, MA, USA.
Sohail ChaudhryClinical Development, Nektar Therapeutics, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Time-to-event endpoints, such as progression free survival (PFS) and overall survival (OS), are critical in assessing therapeutic efficacy in oncology drug development. However, their quality and interpretability are frequently challenged by a range of factors, from protocol design and intercurrent events (ICE) to inconsistent data collection and missing follow-up data. These methodological and operational complexities can obscure the true treatment effect. Discontinuation of study treatment, initiation of subsequent anticancer therapy, lost to follow-up and withdrawal of consent can introduce significant bias, limiting the robustness of survival endpoints and complicating regulatory decision making. Adopting a prospective ICH E9(R1) estimand framework helps mitigate risks associated with data collection, analysis methodology and interpretability. This facilitates clearer discussions with regulators and stakeholders. Although both the FDA guidance on oncology endpoints and the EMA guideline on anticancer medicinal product evaluation outline key principles in evaluating PFS and OS endpoints, integration of ICH E9(R1) offers a harmonized strategy that is important for the design and conduct of randomized late phase oncology clinical trials. In this article, we investigate the quality and interpretability of the endpoints of PFS and OS according to the ICH E9(R1) framework and present some practical recommendations for designing and conducting robust oncology clinical trials.

Indexed as

Antineoplastic AgentsClinical Trials as TopicNeoplasmsProgression-Free SurvivalHumansRandomized Controlled Trials as TopicResearch DesignAntineoplastic AgentsEstimandICH E9 (R1)Intercurrent eventSensitivity analysisSupplementary analysisTipping point analysis

Identifiers

PMID40762767

What OpenQuestion holds

Textmetadata
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.