Evidence map›Paper›PMID 27815768›Full record

ArticleEndocrine2017

Diabetes and kidney cancer outcomes: a propensity score analysis.

Madhur Nayan, Antonio Finelli, Michael A S Jewett, David N Juurlink, Peter C Austin, Girish S Kulkarni, Robert J Hamilton

Abstract read
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In one paragraph

Article in Endocrine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.1field-weighted citation impact, top 19% 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

6 citing papers in PubMed, 10 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. The value of complementing administrative data with abstracted information on smoking and obesity: A study in kidney cancer.Canadian Urological Association journal = Journal de l'Association des urologues du Canada · 2017
    Article
  6. 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

7 authors at 5 institutions in 1 country.

Madhur NayanDivision of Urology, Departments of Surgery and Surgical Oncology, Princess Margaret Cancer Centre, University Health Network and the University of Toronto, Toronto, ON, Canada.
Antonio FinelliDivision of Urology, Departments of Surgery and Surgical Oncology, Princess Margaret Cancer Centre, University Health Network and the University of Toronto, Toronto, ON, Canada.
Michael A S JewettDivision of Urology, Departments of Surgery and Surgical Oncology, Princess Margaret Cancer Centre, University Health Network and the University of Toronto, Toronto, ON, Canada.
David N JuurlinkDepartment of Internal Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada.
Peter C AustinInstitute for Clinical Evaluative Sciences, Toronto, ON, Canada.
Girish S KulkarniDivision of Urology, Departments of Surgery and Surgical Oncology, Princess Margaret Cancer Centre, University Health Network and the University of Toronto, Toronto, ON, Canada.
Robert J HamiltonDivision of Urology, Departments of Surgery and Surgical Oncology, Princess Margaret Cancer Centre, University Health Network and the University of Toronto, Toronto, ON, Canada. rob.hamilton@uhn.ca.
University of Toronto · CAPrincess Margaret Cancer Centre · CASunnybrook Health Science Centre · CASunnybrook Research InstituteUniversity Health Network · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is conflicting evidence whether diabetes is associated with survival outcomes in patients undergoing a nephrectomy for renal cell carcinoma. We performed a retrospective review of 1034 patients undergoing nephrectomy for unilateral, M0, renal cell carcinoma between 2000 and 2016 at a tertiary academic center. Inverse probability of treatment weights were derived from a propensity score model based on various clinical, surgical, and pathological characteristics. We used Cox proportional hazard models to evaluate the association between diabetes and disease-free survival, cancer-specific survival, and overall survival in the sample weighted by the inverse probability of treatment weights. Furthermore, to evaluate whether severity of diabetes was associated with survival outcomes, we performed separate analyses where inverse probability of treatment weights were computed based on the probability of having diabetes that was controlled by medication. Of the 1034 patients, 180 (17 %) had diabetes. Of these, 139 (77 %) patients required medications for diabetes control while the remaining 41 (23 %) had diet controlled diabetes. Median follow-up was 50 months (IQR 17-86). Diabetes at the time of surgery was not significantly associated with disease-free survival (HR 1.11, 95 % CI 0.64 -1.91), cancer-specific survival (HR 0.96, 95 % CI 0.49-1.91), or overall survival (HR 1.28, 95 % CI 0.84-1.95). We found similar results when we compared diabetics controlled with medication vs. non-diabetics or diet controlled diabetics. In summary, we found no significant association between diabetes and survival outcomes in patients undergoing nephrectomy for M0 renal cell carcinoma. These results suggest that diabetics should be treated and followed in a similar manner to non-diabetics.

Indexed as

NephrectomyAdultAgedCarcinoma, Renal CellDiabetes MellitusDisease-Free SurvivalFemaleHumansHypoglycemic AgentsKidney NeoplasmsMaleMiddle AgedPrognosisPropensity ScoreRetrospective StudiesSurvival RateHypoglycemic AgentsDiabetes mellitusKidney neoplasmsNephrectomyPropensity scoreSurvival

Identifiers

PMID27815768
OpenAlexW2548768084

What OpenQuestion holds

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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.