Evidence map›Paper›PMID 42231792›Full record

ArticleJNCI cancer spectrum2026

Clinico-genomic nomograms for estimation of survival risk in metastatic castrate-resistant prostate cancer.

Manish Kohli, Anushka Shankar, Jennifer Lloyd, Liang Wang, Xingyue Huo, Muhammad Zaki Fadlullah, Aik Choon Tan, Joseph Finkelstein

Abstract read
In one paragraph

Article in JNCI cancer spectrum, 2026. 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

8 authors.

Manish KohliDivision of Oncology, Department of Medicine, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, United States.ORCID 0000-0002-9735-6614
Anushka ShankarDivision of Oncology, Department of Medicine, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, United States.ORCID 0000-0002-7019-5494
Jennifer LloydCollege of Nursing, University of Utah, Salt Lake City, UT, United States.ORCID 0000-0002-5566-167X
Liang WangDepartment of Tumor Biology, H. Lee Moffitt Cancer Center, Tampa, FL, United States.ORCID 0000-0002-9364-8572
Xingyue HuoArizona Center for Telemedicine and Digital Health, Department of Medicine, Division of General Internal Medicine, Geriatrics and Palliative Medicine, College of Medicine - Tucson, University of Arizona, Tucson, AZ, United States.
Muhammad Zaki FadlullahDepartment of Oncological Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, United States.
Aik Choon TanDepartment of Oncological Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, United States.ORCID 0000-0003-2955-8369
Joseph FinkelsteinArizona Center for Telemedicine and Digital Health, Department of Medicine, Division of General Internal Medicine, Geriatrics and Palliative Medicine, College of Medicine - Tucson, University of Arizona, Tucson, AZ, United States.ORCID 0000-0002-8084-7441

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo enhance risk stratification in metastatic castrate-resistant prostate cancer (mCRPC), we developed clinical and integrated clinico-genomic prognostic nomograms combining clinical prognostic factors with copy number alteration-based risk scores (RSs) in circulating tumor DNA (ctDNA) and metastatic tissue to predict 1-, 2-, and 3-year overall survival (OS) probabilities.

methodsA clinical prognostic nomogram was developed from publicly accessed Yale University Open Data Access (YODA) data-sciences project (N = 1088 patients). A second publicly available independent dataset (N = 82) with an 11-gene prognostic RS developed concurrently obtained ctDNA and matched metastatic tissue specimens (gains: AR, MYC, COL22A1, PIK3CA, PIK3CB, NOTCH1; losses: TMPRSS2, NCOR1, ZBTB18, TP53, NKX3-1) was used to develop an integrated clinico-genomic survival nomogram. Independent predictors for survival were identified in each dataset using univariate and multivariate Cox proportional hazard. Multivariate regression coefficients with statistical significance (P < .05) were used to develop prognostic nomograms to estimate 1-, 2- and 3-year OS probabilities. Nomogram performances were assessed using time-dependent area under curves (t-AUCs). All analyses were conducted in RStudio (v4.1.2).

resultsThe YODA dataset t-AUCs for the prognostic nomogram for estimating OS at 1, 2, and 3 years were 0.74, 0.70, and 0.74. In the independent second dataset, the integrated clinico-genomic prognostic nomogram was observed to have higher t-AUCs for predicting 3-year mCRPC survival at 0.807 compared with 0.714 using clinical factors alone.

conclusionsAn integrated clinico-genomic nomogram with ctDNA RSs achieved the highest t-AUC for 3-year survival in mCRPC and may enable precision in identification of poor-prognosis subgroups based on somatic alterations.

Indexed as

Circulating Tumor DNANomogramsProstatic Neoplasms, Castration-ResistantAgedDNA Copy Number VariationsGenomicsHumansMaleMiddle AgedNeoplasm MetastasisPrognosisProportional Hazards ModelsRisk AssessmentCirculating Tumor DNA

Identifiers

PMID42231792
PMCPMC13231001

What Socratic 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 Socratic graph.