Evidence map›Paper›PMID 27419632›Full record

ArticleOncotarget2016

An appraisal of drug development timelines in the Era of precision oncology.

Denis Leonardo Jardim, Maria Schwaederle, David S Hong, Razelle Kurzrock

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.7field-weighted citation impact, top 17% 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

13 citing papers in PubMed, 34 citations in OpenAlex.

  1. Article
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  9. Article
  10. Cell-free DNA in cancer: current insights.Cellular oncology (Dordrecht, Netherlands) · 2019
    Review
  11. Review
  12. Review
  13. Analysis of Drug Development Paradigms for Immune Checkpoint Inhibitors.Clinical cancer research : an official journal of the American Association for Cancer Research · 2018
    Review
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

4 authors at 3 institutions in 2 countries.

Denis Leonardo JardimDepartment of Clinical Oncology, Hospital Sirio Libanes, Sao Paulo, Brazil.
Maria SchwaederleCenter for Personalized Cancer Therapy and Division of Hematology and Oncology, University of California, San Diego, CA, USA.
David S HongDepartment of Investigational Cancer Therapeutics (Phase I Clinical Trials Program), The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Razelle KurzrockCenter for Personalized Cancer Therapy and Division of Hematology and Oncology, University of California, San Diego, CA, USA.
University of California, San Diego · USHospital Sírio-Libanês · BRThe University of Texas MD Anderson Cancer Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The effects of incorporating a biomarker-based (personalized or precision) selection strategy on drug development timelines for new oncology drugs merit investigation. Here we accessed documents from the Food and Drug Administration (FDA) database for anticancer agents approved between 09/1998 and 07/2014 to compare drugs developed with and without a personalized strategy. Sixty-three drugs were included (28 [44%] personalized and 35 [56%] non-personalized). No differences in access to FDA-expedited programs were observed between personalized and non-personalized drugs. A personalized approach for drug development was associated with faster clinical development (Investigational New Drug [IND] to New Drug Application [NDA] submission; median = 58.8 months [95% CI 53.8-81.8] vs. 93.5 months [95% CI 73.9-112.9], P =.001), but a similar approval time (NDA submission to approval; median=6.0 months [95% CI 5.5-8.4] vs. 6.1 months [95% CI 5.9-8.3], P = .756) compared to a non-personalized strategy. In the multivariate model, class of drug stratified by personalized status (targeted personalized vs. targeted non-personalized vs. cytotoxic) was the only independent factor associated with faster total time of clinical drug development (clinical plus approval phase, median = 64.6 vs 87.1 vs. 112.7 months [cytotoxic], P = .038). Response rates (RR) in early trials were positively correlated with RR in registration trials (r = 0.63, P = <.001), and inversely associated with total time of drug development (r = -0.29, P = .049). In conclusion, targeted agents were developed faster than cytotoxic agents. Shorter times to approval were associated, in multivariate analysis, with a biomarker-based clinical development strategy.

Indexed as

Antineoplastic AgentsDrug ApprovalDrugs, InvestigationalHumansMedical OncologyPrecision MedicineTime FactorsUnited StatesUnited States Food and Drug AdministrationAntineoplastic AgentsDrugs, Investigationalbiomarkersdrug developmentFDApharmacoeconomicsprecision medicine

Identifiers

PMID27419632
PMCPMC5288167
OpenAlexW2470830961

What OpenQuestion holds

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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.