Evidence map›Paper›PMID 31918457›Full record

ArticleCancer medicine2020

Assessment of variation in 30-day mortality following cancer surgeries among older adults across US hospitals.

Allison Lipitz-Snyderman, Jessica A Lavery, Peter B Bach, Diane G Li, Annie Yang, Vivian E Strong, Ashley Russo, Katherine S Panageas

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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Observational
  2. Current therapeutic options for gastric adenocarcinoma.Saudi journal of biological sciences · 2021
    Review
  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

8 authors.

Allison Lipitz-SnydermanCenter for Health Policy and Outcomes, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.ORCID 0000-0003-2423-2220
Jessica A LaveryBiostatistics Service, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.ORCID 0000-0002-2746-5647
Peter B BachCenter for Health Policy and Outcomes, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Diane G LiCenter for Health Policy and Outcomes, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Annie YangCenter for Health Policy and Outcomes, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.ORCID 0000-0001-5368-1514
Vivian E StrongDepartment of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Ashley RussoDepartment of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Katherine S PanageasBiostatistics Service, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Elisa de Stanchina · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

backgroundWhile public reporting of surgical outcomes for noncancer conditions is common, cancer surgeries have generally been excluded. This is true despite numerous studies showing outcomes to differ between hospitals based on their characteristics. Our objective was to assess whether three prerequisites for quality assessment and reporting are present for 30-day mortality after cancer surgery: low burden for timely reporting, hospital variation, and potential for public health gains. STUDY

designWe used Fee-for-Service (FFS) Medicare claims to examine the extent of variation in 30-day cancer surgical mortality between 3860 US hospitals. We included 340 489 surgeries for 12 cancer types for FFS Medicare beneficiaries aged ≥66 years, 2011-2013. Hierarchical mixed-effects logistic regression models adjusted for patient and hospital characteristics and with a random hospital effect were fit to obtain hospital-specific risk-standardized mortality rates (RSMRs) and 99% confidence intervals (CI). We calculated a hospital odds ratio to describe the difference in mortality risk for a hospital above vs below average quality and estimated the potential mortality reduction.

resultsThe median number of cancer surgeries per hospital was 34. The median RSMR overall was 2.41% (99% CI 2.28%, 2.66%). In aggregate and for most cancers, variation between hospitals exceeded that due to differences in patient and hospital characteristics. For individual cancers, relative differences exceeded 20% in mortality risk between patients undergoing surgery at a hospital below vs above average quality, with the potential for an estimated 500 deaths prevented annually given hypothetical improvements.

conclusionQuality measurement and reporting of 30-day mortality for cancer surgery is worthy of consideration.

Indexed as

Hospital MortalityAdministrative Claims, HealthcareAgedAged, 80 and overFee-for-Service PlansFemaleHumansMaleMedicareNeoplasmsOdds RatioQuality ImprovementQuality Indicators, Health CareRisk AssessmentRisk FactorsUnited Statescomplicationshealth careoutcomes assessment (health care)quality indicatorsquality of health caresurgery

Identifiers

PMID31918457
PMCPMC7050094

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LicenceCC BY
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Registered trials

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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.