Evidence map›Paper›PMID 32100417›Full record

ArticleCancer medicine2020

Novel risk group stratification for metastatic urothelial cancer patients treated with immune checkpoint inhibitors.

Julie M Shabto, Dylan J Martini, Yuan Liu, Deepak Ravindranathan, Jacqueline Brown, Emilie E Hitron, Greta A Russler, Sarah Caulfield, Haydn Kissick, Mehrdad Alemozaffar and 6 more

Abstract read
In one paragraph

Article in Cancer medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 pooled it
–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

13 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. 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

16 authors.

Julie M ShabtoDepartment of Hematology and Medical Oncology, Emory University School of Medicine, Atlanta, GA, USA.ORCID 0000-0003-0991-9294
Dylan J MartiniDepartment of Hematology and Medical Oncology, Emory University School of Medicine, Atlanta, GA, USA.ORCID 0000-0002-0843-1222
Yuan LiuDepartments of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA.
Deepak RavindranathanWinship Cancer Institute of Emory University, Atlanta, GA, USA.
Jacqueline BrownDepartment of Hematology and Medical Oncology, Emory University School of Medicine, Atlanta, GA, USA.
Emilie E HitronWinship Cancer Institute of Emory University, Atlanta, GA, USA.
Greta A RusslerDepartment of Hematology and Medical Oncology, Emory University School of Medicine, Atlanta, GA, USA.
Sarah CaulfieldDepartment of Hematology and Medical Oncology, Emory University School of Medicine, Atlanta, GA, USA.
Haydn KissickWinship Cancer Institute of Emory University, Atlanta, GA, USA.
Mehrdad AlemozaffarWinship Cancer Institute of Emory University, Atlanta, GA, USA.
Kenneth OganWinship Cancer Institute of Emory University, Atlanta, GA, USA.ORCID 0000-0001-7715-3724
Wayne B HarrisDepartment of Hematology and Medical Oncology, Emory University School of Medicine, Atlanta, GA, USA.
Viraj A MasterDepartment of Urology, Emory University School of Medicine, Atlanta, GA, USA.ORCID 0000-0002-7251-142X
Omer KucukDepartment of Hematology and Medical Oncology, Emory University School of Medicine, Atlanta, GA, USA.ORCID 0000-0002-4755-0507
Bradley C CarthonDepartment of Hematology and Medical Oncology, Emory University School of Medicine, Atlanta, GA, USA.
Mehmet A BilenDepartment of Hematology and Medical Oncology, Emory University School of Medicine, Atlanta, GA, USA.ORCID 0000-0003-4003-1103

Funding

Winship Cancer Institute Cancer Center Support GrantP30CA138292 · NCI · EMORY UNIVERSITY · PI Suresh S Ramalingam · 2009 to 2026
$47.5M
NCI NIH HHS P30 CA138292
6 · The paper itself

Abstract

backgroundWe developed a novel risk scoring system for urothelial cancer (UC) patients receiving immune checkpoint inhibitors (ICI).

methodsWe conducted a retrospective review of 67 UC patients treated with ICI at Winship Cancer Institute of Emory University from 2015 to 2018. Using stepwise variable selection in Cox proportional hazard model and Sullivan's weighting schema, baseline platelet-to-lymphocyte ratio (PLR), presence of liver metastasis, baseline albumin, and baseline Eastern Cooperative Oncology Group performance status (ECOG PS) were used for risk scoring. Patients were categorized into good risk (risk score 0-1), intermediate risk (risk score 2-3), and poor risk (risk score 4-6). Univariable (UVA) and multivariable analysis (MVA) and Kaplan-Meier method were used to assess overall survival (OS) and progression free survival (PFS).

resultsThe Emory Risk Scoring System had C-statistics of 0.74 (Standard Error = 0.047) in predicting OS and 0.70 (Standard Error = 0.043) in predicting PFS. Compared to good risk patients, poor risk patients had significantly shorter OS and PFS in both UVA and MVA (all P < .001), and intermediate risk patients had significantly shorter OS and PFS in both UVA and MVA (all P < .03).

conclusionsRisk scoring using baseline PLR, presence of liver metastasis, baseline albumin, and baseline ECOG PS may effectively predict OS and PFS in UC patients receiving ICI.

Indexed as

AdultAgedAged, 80 and overFemaleFollow-Up StudiesHumansImmune Checkpoint InhibitorsLiver NeoplasmsMaleMiddle AgedPrognosisRetrospective StudiesRisk AssessmentRisk FactorsSurvival RateUrologic NeoplasmsImmune Checkpoint Inhibitorscancer risk factorsimmunologyrisk assessmenturological oncology

Identifiers

PMID32100417
PMCPMC7163104

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.