Evidence map›Paper›PMID 28652451›Full record

ArticleIn vivo (Athens, Greece)

A New Prognostic Tool for Patients Undergoing Radiotherapy plus Upfront Transurethral Resection for Bladder Cancer.

Lisa Manig, Stefan Janssen, Steven E Schild, Dirk Rades

Open access · diamondAbstract read
In one paragraph

Article in In vivo (Athens, Greece). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 23% 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

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. 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

4 authors at 2 institutions in 2 countries.

Lisa ManigDepartment of Radiation Oncology, University of Lübeck, Lübeck, Germany.
Stefan JanssenDepartment of Radiation Oncology, University of Lübeck, Lübeck, Germany.
Steven E SchildDepartment of Radiation Oncology, Mayo Clinic, Scottsdale, AZ, U.S.A.
Dirk RadesDepartment of Radiation Oncology, University of Lübeck, Lübeck, Germany rades.dirk@gmx.net.
University of Lübeck · DEMayo Clinic in Arizona · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo create a tool to estimate overall survival (OS) of patients with non-metastatic bladder cancer. PATIENTS AND

methodsEight parameters were retrospectively evaluated for OS in 42 patients undergoing radiotherapy and upfront transurethral resection for bladder cancer. The prognostic tool included those parameters that were significant on both univariate and multivariate analyses. The tool was based on the 3-year OS rate divided by 10. Patient scores were calculated by adding the points for each significant parameter.

resultsOn univariate analysis, 3-year OS was associated with gender (p=0.017), pack years (p=0.009) and Karnofsky performance score (KPS) (p<0.001). On Cox regression, pack years (p=0.007) and KPS (p<0.001) remained significant and were incorporated into the tool. Three prognostic groups were designated with 6, 10-11 and 15 points with 3-year OS-rates of 0%, 34% and 83%, respectively (p<0.001).

conclusionA tool was developed to estimate the OS of patients with bladder cancer to improve individualization of treatment.

Indexed as

PrognosisAgedAged, 80 and overDisease-Free SurvivalFemaleHumansKaplan-Meier EstimateKarnofsky Performance StatusMaleTreatment OutcomeUrinary Bladder NeoplasmsBladder canceroverall survivalprognostic toolradiotherapytransurethral resection

Identifiers

PMID28652451
PMCPMC5566934
OpenAlexW2647132818

What OpenQuestion holds

Textmetadata
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.