Evidence map›Paper›PMID 42150920›Full record

ArticleUrologic oncology2026

Evaluation of algorithms for predicting new baseline renal function after complex partial nephrectomy for multifocal renal tumors.

Nityam Rathi, Lauren Loebach, Braden Millan, Milan H Patel, Ruben Blachman-Braun, Daniel Nethala, Abhinav Khanna, Sandeep Gurram, W Marston Linehan, Mark W Ball

Abstract read
In one paragraph

Article in Urologic oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Nityam RathiDepartment of Urology, Mayo Clinic, Rochester, MN, USA.
Lauren LoebachUrologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Braden MillanUrologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Milan H PatelUrologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Ruben Blachman-BraunUrologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Daniel NethalaUrologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Abhinav KhannaDepartment of Urology, Mayo Clinic, Rochester, MN, USA.
Sandeep GurramUrologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
W Marston LinehanUrologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Mark W BallUrologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. Electronic address: mark.ball@nih.gov.

Funding

Intramural NIH HHS Z99 CA999999
6 · The paper itself

Abstract

introductionPartial nephrectomy (PN) for localized renal cancer is associated with favorable survival outcomes due to preservation of renal function. Approaches for predicting new-baseline-GFR (NBGFR) after PN have been proposed, including multivariable algorithms and a formula presuming that 90% of the renal parenchyma is preserved during PN. However, these models were developed from cohorts with sporadic single-tumor renal cancer. We evaluate these predictive models in patients undergoing PN for multifocal disease. Accurate prediction of NBGFR has major implications in these patients, as they may require multiple PN for metachronous kidney cancer.

methodsPatients who underwent PN for removal of ≥2 tumors from 2006 to 2024 and had available measurements of preop/postoperative GFR were considered. The final cohort included 453 patients, of whom 184 underwent multiple PN. Four predictive models were evaluated. Model performance was assessed using correlation-coefficient(r) and mean-squared-error (MSE).

resultsApproximately 30% of patients had sporadic, multifocal renal tumors, and 70% had hereditary renal cancer. The 90% formula had a higher r and lower MSE values compared to the multivariable models, and also showed improved accuracy, bias, and precision. In patients undergoing multiple PN, 85% to 91% of the GFR was preserved in each PN.

conclusionsModels for predicting NBGFR after PN showed strong performance in our cohort with multifocal renal tumors. The conceptually simple formula presuming 90% renal parenchymal preservation, and thus 90% GFR preservation, most accurately predicted NBGFR. The %GFR preserved with each PN remained stable across sequential PN. These findings suggest that preservation of renal parenchyma is a relevant determinant of NBGFR after PN for multifocal tumors.

Indexed as

AlgorithmsKidneyKidney NeoplasmsNephrectomyAgedFemaleGlomerular Filtration RateHumansMaleMiddle AgedHereditary Renal CancerMultifocal Renal TumorsNew Baseline Glomerular Filtration RatePartial Nephrectomy

Identifiers

PMID42150920
PMCPMC13284857

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.