Evidence map›Paper›PMID 28693428›Full record

ArticleBMC medical research methodology2017

Inverse probability of treatment-weighted competing risks analysis: an application on long-term risk of urinary adverse events after prostate cancer treatments.

Charlotte A Bolch, Haitao Chu, Stephanie Jarosek, Stephen R Cole, Sean Elliott, Beth Virnig

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medical research methodology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
13.2field-weighted citation impact, top 2% 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

21 citing papers in PubMed, 41 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

6 authors at 2 institutions in 1 country.

Charlotte A BolchUniversity of Minnesota, Twin Cities Campus, 3 Morrill Hall, 100 Church St. S.E, Minneapolis, MN, 55455, USA. cbolch@ufl.edu.ORCID http://orcid.org/0000-0002-9797-6557
Haitao ChuUniversity of Minnesota, Twin Cities Campus, 3 Morrill Hall, 100 Church St. S.E, Minneapolis, MN, 55455, USA.
Stephanie JarosekUniversity of Minnesota, Twin Cities Campus, 3 Morrill Hall, 100 Church St. S.E, Minneapolis, MN, 55455, USA.
Stephen R ColeUniversity of North Carolina, Chapel Hill, 2105E McGavran-Greenberg Hall, CB #7435, Chapel Hill, NC, 27599, USA.
Sean ElliottUniversity of Minnesota, Twin Cities Campus, 3 Morrill Hall, 100 Church St. S.E, Minneapolis, MN, 55455, USA.
Beth VirnigUniversity of Minnesota, Twin Cities Campus, 3 Morrill Hall, 100 Church St. S.E, Minneapolis, MN, 55455, USA.
University of Minnesota · USUniversity of North Carolina at Chapel Hill · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo illustrate the 10-year risks of urinary adverse events (UAEs) among men diagnosed with prostate cancer and treated with different types of therapy, accounting for the competing risk of death.

methodsProstate cancer is the second most common malignancy among adult males in the United States. Few studies have reported the long-term post-treatment risk of UAEs and those that have, have not appropriately accounted for competing deaths. This paper conducts an inverse probability of treatment (IPT) weighted competing risks analysis to estimate the effects of different prostate cancer treatments on the risk of UAE, using a matched-cohort of prostate cancer/non-cancer control patients from the Surveillance, Epidemiology and End Results (SEER) Medicare database.

resultsStudy dataset included men age 66 years or older that are 83% white and had a median follow-up time of 4.14 years. Patients that underwent combination radical prostatectomy and external beam radiotherapy experienced the highest risk of UAE (IPT-weighted competing risks: HR 3.65 with 95% CI (3.28, 4.07); 10-yr. cumulative incidence = 36.5%).

conclusionsFindings suggest that IPT-weighted competing risks analysis provides an accurate estimator of the cumulative incidence of UAE taking into account the competing deaths as well as measured confounding bias.

Indexed as

AgedAged, 80 and overCohort StudiesHumansIncidenceKaplan-Meier EstimateMaleMedicareOutcome Assessment, Health CarePropensity ScoreProportional Hazards ModelsProstatectomyProstatic NeoplasmsRadiotherapyRisk FactorsSEER ProgramCompeting risksConfounding biasInverse probability weightingProstate cancerSurvival analysisUrinary adverse events

Identifiers

PMID28693428
PMCPMC5504854
OpenAlexW2735312806

What OpenQuestion 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 OpenQuestion graph.