Evidence map›Paper›PMID 31411983›Full record

ArticleEuropean urology oncology2019

Impact of Hospital Case Volume on Outcomes Following Radical Nephrectomy and Inferior Vena Cava Thrombectomy.

Yuval Freifeld, Solomon L Woldu, Nirmish Singla, Timothy Clinton, Aditya Bagrodia, Ryan Hutchinson, Yair Lotan, Vitaly Margulis

Open access · greenAbstract read
In one paragraph

Article in European urology oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.8field-weighted citation impact, top 14% 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

15 citing papers in PubMed, 33 citations in OpenAlex.

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  9. A novel technique for proximal inferior vena cava control during tumor thrombectomy using the COBRA-OS balloon.Canadian Urological Association journal = Journal de l'Association des urologues du Canada · 2024
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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 at 1 institution in 1 country.

Yuval FreifeldDepartment of Urology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Solomon L WolduDepartment of Urology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Nirmish SinglaDepartment of Urology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Timothy ClintonDepartment of Urology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Aditya BagrodiaDepartment of Urology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Ryan HutchinsonDepartment of Urology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Yair LotanDepartment of Urology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Vitaly MargulisDepartment of Urology, University of Texas Southwestern Medical Center, Dallas, TX, USA. Electronic address: vitaly.margulis@utsouthwestern.edu.
The University of Texas Southwestern Medical Center · US

Funding

Physician Scientist Oncology Training ProgramT32CA136515 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI SKAPEK, STEPHEN X · 2009 to 2018
$2.2M
NCI NIH HHS T32 CA136515
6 · The paper itself

Abstract

backgroundRadical nephrectomy with inferior vena cava thrombectomy (RN-IVCT) is a complicated procedure for which the impact of hospital case volume on overall survival (OS) is unknown.

objectiveTo assess the degree to which renal cell carcinoma (RCC) with inferior vena cava tumor thrombus (IVC-TT) care is centralized and to evaluate the impact of hospital case volume on outcomes following RN-IVCT. DESIGN, SETTING, AND

participantsThe National Cancer Data Base was queried for patients with pT3b-c RCC treated with RN-IVCT. Hospitals were classified by case volume percentile as low (<75th percentile, <0.67 cases annually), intermediate (75th-95th percentile, 0.67-2.99 cases annually), or high (>95th percentile, >3 cases annually). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The primary outcome was OS. Secondary outcomes were short-term (30- and 90-d) mortality rates according to hospital case volume. Kaplan-Meier curves and Cox regression model were used to evaluate OS and the effect of covariables. RESULTS AND LIMITATIONS: There were 2664 cases of RN-IVCT for pT3b-c tumors reported by 573 institutions, of which 435, 108, and 30 were classified as low, intermediate, and high volume, accounting for 28.5%, 34.5%, and 37% of cases, respectively. Treatment at high-volume institutions was associated with better OS: the median OS was 42, 53, and 60 months for low, intermediate and high-volume centers, respectively (p=0.009). After multivariable adjustment, treatment at a high-volume institution was associated with a 24% relative risk reduction for all-cause mortality compared to treatment at a low-volume institution (hazard ratio 0.76, 95% confidence interval 0.65-0.89; p=0.001). There was no significant difference in short-term mortality following RN-IVCT when stratified by hospital case volume.

conclusionsHigher hospital case volume was associated with longer OS for patients undergoing RN-IVCT. These findings support efforts to centralize care for cases of advanced RCC. PATIENT SUMMARY: In this study we looked at the impact of hospital case volume on survival following surgery for renal cell carcinoma and inferior vena cava thrombectomy. Survival was significantly better in high-volume hospitals performing three or more procedures per year.

Indexed as

AdultAgedCarcinoma, Renal CellFemaleHospitals, High-VolumeHumansKidney NeoplasmsMaleMiddle AgedNephrectomyThrombectomyTreatment OutcomeVena Cava, InferiorVenous ThrombosisHospital volumeInferior vena cavaNephrectomyRenal cell carcinomaSurvivalThrombectomyTumor thrombus

Identifiers

PMID31411983
PMCPMC6697235
OpenAlexW2900575912

What OpenQuestion holds

Textmetadata
LicenceTDM
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.