Evidence map›Paper›PMID 30644815›Full record

ArticleRadiology2019

Personalized Treatment for Small Renal Tumors: Decision Analysis of Competing Causes of Mortality.

Stella K Kang, William C Huang, Elena B Elkin, Pari V Pandharipande, R Scott Braithwaite

Open access · hybridAbstract read
In one paragraph

Article in Radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.7field-weighted citation impact, top 15% 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

4 citing papers in PubMed, 14 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. 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

5 authors at 1 institution in 1 country.

Stella K KangFrom the Departments of Radiology (S.K.K.), Population Health (S.K.K., R.S.B.), Urology (W.C.H.), and Medicine (R.S.B.), NYU School of Medicine, 550 First Ave, New York, NY 10016; Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY (E.B.E.); and Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital, Boston, Mass (P.V.P.).ORCID 0000-0003-2402-3787
William C HuangFrom the Departments of Radiology (S.K.K.), Population Health (S.K.K., R.S.B.), Urology (W.C.H.), and Medicine (R.S.B.), NYU School of Medicine, 550 First Ave, New York, NY 10016; Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY (E.B.E.); and Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital, Boston, Mass (P.V.P.).
Elena B ElkinFrom the Departments of Radiology (S.K.K.), Population Health (S.K.K., R.S.B.), Urology (W.C.H.), and Medicine (R.S.B.), NYU School of Medicine, 550 First Ave, New York, NY 10016; Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY (E.B.E.); and Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital, Boston, Mass (P.V.P.).
Pari V PandharipandeFrom the Departments of Radiology (S.K.K.), Population Health (S.K.K., R.S.B.), Urology (W.C.H.), and Medicine (R.S.B.), NYU School of Medicine, 550 First Ave, New York, NY 10016; Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY (E.B.E.); and Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital, Boston, Mass (P.V.P.).ORCID 0000-0002-2855-9119
R Scott BraithwaiteFrom the Departments of Radiology (S.K.K.), Population Health (S.K.K., R.S.B.), Urology (W.C.H.), and Medicine (R.S.B.), NYU School of Medicine, 550 First Ave, New York, NY 10016; Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY (E.B.E.); and Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital, Boston, Mass (P.V.P.).
Memorial Sloan Kettering Cancer Center · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Elisa de Stanchina · 1985 to 2026
$347.4M
Patient-Centered Decision-Making for Management of Small Renal Tumors - SupplementK07CA197134 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI KANG, STELLA · 2016 to 2021
$1.0M
NCI NIH HHS K07 CA197134NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

Purpose To compare the effectiveness of personalized treatment for small (≤4 cm) renal tumors versus routine partial nephrectomy (PN), accounting for various competing causes of mortality. Materials and Methods A state-transition microsimulation model was constructed to compare life expectancy of management strategies for small renal tumors by using 1 000 000 simulations in the following ways: routine PN or personalized treatment involving percutaneous ablation for risk factors for worsening chronic kidney disease (CKD), and otherwise PN; biopsy, with triage of renal cell carcinoma (RCC) to PN or ablation depending on risk factors for worsening CKD; active surveillance for growth; and active surveillance when MRI findings are indicative of papillary RCC. Transition probabilities were incorporated from the literature. Effects of parameter variability were assessed in sensitivity analysis. Results In patients of all ages with normal renal function, routine PN yielded the longest life expectancy (eg, 0.67 years in 65-year-old men with nephrometry score [NS] of 4). Otherwise, personalized strategies extended life expectancy versus routine PN: in CKD stages 2 or 3a, moderate or high NS, and no comorbidities, MRI guidance for active surveillance extended life expectancy (eg, 2.60 years for MRI vs PN in CKD 3a, NS 10); and with Charlson comorbidity index of 1 or more, biopsy or active surveillance for growth extended life expectancy (eg, 2.70 years for surveillance for growth in CKD 3a, NS 10). CKD 3b was most effectively managed by using MRI to help predict papillary RCC for surveillance. Conclusion For patients with chronic kidney disease and small renal tumors, personalized treatment selection likely extends life expectancy. © RSNA, 2019 Online supplemental material is available for this article.

Indexed as

Decision Support TechniquesLife ExpectancyPrecision MedicineAgedBiopsyCarcinoma, Renal CellCatheter AblationDisease ProgressionFemaleHumansKidney Function TestsKidney NeoplasmsMagnetic Resonance ImagingMaleMiddle AgedNeoplasm Staging

Identifiers

PMID30644815
PMCPMC6394736
OpenAlexW2909278596

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.