Evidence map›Paper›PMID 33531652›Full record

ArticleProstate cancer and prostatic diseases2021

Predicting toxicity-related docetaxel discontinuation and overall survival in metastatic castration-resistant prostate cancer: a pooled analysis of open phase 3 clinical trial data.

Alberto Martini, Anish B Parikh, John P Sfakianos, Francesco Montorsi, Matthew D Galsky, William K Oh, Che-Kai Tsao

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In one paragraph

Article in Prostate cancer and prostatic diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

6 citing papers in PubMed, 9 citations in OpenAlex.

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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

7 authors at 3 institutions in 2 countries.

Alberto Martini *Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY, USA. a.martini.md@gmail.com.ORCID http://orcid.org/0000-0003-1272-7154
Anish B Parikh *Genitourinary Oncology Section, Division of Medical Oncology, The Ohio State University Comprehensive Cancer Center - James Cancer Hospital, Columbus, OH, USA.
John P SfakianosDepartment of Urology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Francesco MontorsiDepartment of Urology, Vita-Salute San Raffaele University, Milan, Italy.
Matthew D GalskyDivision of Hematology/Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
William K OhDivision of Hematology/Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID http://orcid.org/0000-0001-5113-8147
Che-Kai TsaoDivision of Hematology/Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Icahn School of Medicine at Mount Sinai · USVita-Salute San Raffaele University · ITThe Ohio State University Comprehensive Cancer Center – Arthur G. James Cancer Hospital and Richard J. Solove Research Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDocetaxel is widely used in metastatic castration-resistant prostate cancer (mCRPC), however its optimal use remains unclear in the current treatment landscape. Biomarkers to predict Docetaxel toxicity may help optimize treatment selection. We aimed to create a predictive model for toxicity-related Docetaxel discontinuation (TRDD).

methodsThrough Project Data Sphere, we accessed individual patient data from the control arms of three frontline mCRPC trials: ASCENT2, VENICE, and MAINSAIL. The inclusion criteria for these trials were all similar and included patients with chemotherapy-naïve mCRPC. The primary outcome was occurrence of TRDD. A competing risks regression (CRR) was used to predict TRDD, after accounting for the occurrence of competing events (death or progression). The output of the model was used as the dependent variable on a classification and regression tree (CART) to identify risk groups for TRDD.

resultsOverall, 1568 patients were considered. Pooled CI of TRDD was 19% after accounting for competing events (death: 474; progression: 59) within 12 months of starting treatment. To build a risk calculator we relied on a CRR that ultimately included age, ECOG performance status, AST, bilirubin, use of analgesics, and presence of diabetes and chronic kidney disease. The CART analysis identified three risk groups that were named: low (model-derived TRDD risk ≤24%), intermediate (25-64%), and high (≥65%) risk group. In each risk group, probability of TRDD during treatment was 14%, 58%, and 79%, and median OS was 24 months, 20 months, and 13 months, respectively (p < 0.001).

conclusionsTreatment selection in mCRPC remains a challenge. Our model can help clinicians balance Docetaxel toxicity and efficacy. The three risk categories that we identified correlated with OS and this is particularly useful for an optimal shared decision-making process.

Indexed as

AgedAntineoplastic AgentsBiomarkers, TumorClinical Trials, Phase III as TopicDocetaxelDrug-Related Side Effects and Adverse ReactionsFollow-Up StudiesHumansMaleMiddle AgedPrognosisProspective StudiesProstatic Neoplasms, Castration-ResistantSurvival RateWithholding TreatmentAntineoplastic AgentsBiomarkers, TumorDocetaxel

Identifiers

PMID33531652
OpenAlexW3127964290

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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.