Evidence map›Paper›PMID 35383004›Full record

ArticleClinical genitourinary cancer2022

Identification and Validation of the Prognostic Impact of Metastatic Prostate Cancer Phenotypes.

Shelby A Labe, Xi Wang, Eric J Lehrer, Amar U Kishan, Daniel E Spratt, Christine Lin, Alicia K Morgans, Lee Ponsky, Jorge A Garcia, Sara Garrett and 2 more

Open access · greenAbstract read
In one paragraph

Article in Clinical genitourinary cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 38% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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

12 authors at 5 institutions in 1 country.

Shelby A LabeDepartment of Radiation Oncology, Penn State Cancer Institute, Hershey, PA.
Xi WangDepartment of Public Health Sciences, Penn State College of Medicine, Hershey, PA.
Eric J LehrerDepartment of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY.
Amar U KishanDepartment of Radiation Oncology, University of California, Los Angeles, CA.
Daniel E SprattDepartment of Radiation Oncology, University Hospitals Cleveland Medical Center, Cleveland, OH.
Christine LinDepartment of Radiation Oncology, Penn State Cancer Institute, Hershey, PA.
Alicia K MorgansDepartment of Medical Oncology, Northwestern University Feinberg School of Medicine, Chicago, IL.
Lee PonskyDepartment of Urology, University Hospitals Cleveland Medical Center, Cleveland, OH.
Jorge A GarciaDepartment of Medical Oncology, University Hospitals Cleveland Medical Center, Cleveland, OH.
Sara GarrettDepartment of Radiation Oncology, Penn State Cancer Institute, Hershey, PA.
Ming WangDepartment of Public Health Sciences, Penn State College of Medicine, Hershey, PA.
Nicholas G ZaorskyDepartment of Medical Oncology, University Hospitals Cleveland Medical Center, Cleveland, OH. Electronic address: nicholas.zaorsky@uhhospitals.org.
Pennsylvania State University · USUniversity Hospitals of Cleveland · USIcahn School of Medicine at Mount Sinai · USNorthwestern University · USUniversity of California, Los Angeles · US

Funding

NCI NIH HHS L30 CA231572
6 · The paper itself

Abstract

introductionCastration-sensitive metastatic prostate cancer is heterogeneous. Our objective is to identify metastatic prostate cancer phenotypes and their prognostic impact on survival. MATERIALS AND

methodsThe National Cancer Database was queried. The Surveillance, Epidemiology, and End Results database was used for validation. Patterns were split into: nonregional lymph node, bone only, and visceral (any brain/liver/lung). Hazard ratios (HR) with 95% confidence intervals (CI) were calculated for the univariate and multivariate Cox proportional hazards regression models, odds ratios were calculated, Kaplan-Meier curves were generated, and a nomogram of the multivariate regression model was created.

resultsThe training set included 13,818 men; bone only was most common (n = 11,632, 84.2%), then nonregional lymph node (n = 1388, 10.0%), and any visceral (brain/liver/lung; n = 798, 5.8%). Risk of death was increased by metastases to a visceral organ versus nonregional lymph node (HR = 2.26; 95% CI [2.00, 2.56]), bone only metastases versus nonregional lymph node (HR = 1.57; 95% CI [1.43, 1.72]), T-stage 4 versus 1 (HR = 1.27; 95% CI [1.17, 1.36]), Grade Group 5 versus 1 (HR = 1.93; 95% CI [1.61, 2.31]), PSA > 20 ng/mL versus < 10 ng/mL (HR = 1.32; 95% CI [1.23, 1.42]), and age ≥ 80 versus < 50 (HR = 1.96; 95% CI [1.69, 2.29]). On internal validation, the model had C-indices 20.5%, 22.7%, and 14.6% higher than the current staging system for overall survival, 1-year, and 5-year survival, respectively.

conclusionWe developed and validated prognostic metastatic prostate cancer phenotypes that can assist risk stratification to potentially personalize therapy. Our nomogram (https://tinyurl.com/prostate-met) may be used to predict survival.

Indexed as

Bone NeoplasmsProstatic NeoplasmsHumansMaleNeoplasm StagingNomogramsPhenotypePrognosisNomogramPrognosisStagingStratificationSurvival

Identifiers

PMID35383004
PMCPMC9329179
OpenAlexW4214735564

What OpenQuestion holds

Textmetadata
LicenceTDM
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.