Evidence map›Paper›PMID 34580027›Full record

ArticleUrologic oncology2022

Clinical laboratory tests associated with survival in patients with metastatic renal cell carcinoma: A Laboratory Wide Association Study (LWAS).

Kyla Velaer, I-Chun Thomas, Jaden Yang, Kristopher Kapphahn, Thomas J Metzner, Abhinav Golla, Christian R Hoerner, Alice C Fan, Viraj Master, Glenn M Chertow and 4 more

Open access · greenAbstract read
In one paragraph

Article in Urologic oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 34% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Observational
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

14 authors at 7 institutions in 1 country.

Kyla VelaerDepartment of Urology, Stanford University School of Medicine, Stanford, CA.
I-Chun ThomasVeterans Affairs Palo Alto Health Care System, Palo Alto, CA.
Jaden YangQuantitative Sciences Unit, Department of Medicine, Stanford University School of Medicine, Stanford, CA.
Kristopher KapphahnQuantitative Sciences Unit, Department of Medicine, Stanford University School of Medicine, Stanford, CA.
Thomas J MetznerDepartment of Urology, Stanford University School of Medicine, Stanford, CA; Pacific Northwest University of Health Sciences, Yakima, WA.
Abhinav GollaDepartment of Ophthalmology, UCLA School of Medicine, Los Angeles, CA.
Christian R HoernerDepartment of Medicine, Stanford University School of Medicine, Stanford, CA.
Alice C FanDepartment of Urology, Stanford University School of Medicine, Stanford, CA; Department of Medicine, Stanford University School of Medicine, Stanford, CA.
Viraj MasterDepartment of Urology, Emory University School of Medicine, Atlanta, GA.
Glenn M ChertowDepartment of Medicine, Stanford University School of Medicine, Stanford, CA.
James D BrooksDepartment of Urology, Stanford University School of Medicine, Stanford, CA.
Chirag J PatelDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA.
Manisha DesaiQuantitative Sciences Unit, Department of Medicine, Stanford University School of Medicine, Stanford, CA.
John T LeppertVeterans Affairs Palo Alto Health Care System, Palo Alto, CA; Department of Urology, Stanford University School of Medicine, Stanford, CA; Department of Medicine, Stanford University School of Medicine, Stanford, CA. Electronic address: jleppert@stanford.edu.
Stanford University · USVA Palo Alto Health Care System · USEmory University · USHarvard University · USPacific Northwest University of Health Sciences · USStanford Medicine · USUniversity of California, Los Angeles · US

Funding

Data science tools to identify robust exposure-phenotype associations for precision medicineR01ES032470 · NIEHS · HARVARD MEDICAL SCHOOL · PI MANRAI, ARJUN KUMAR, PATEL, CHIRAG J. · 2021 to 2025
$3.5M
NIEHS NIH HHS R01 ES032470
6 · The paper itself

Abstract

backgroundPrognostic models for patients with metastatic renal cell carcinoma (mRCC) include select laboratory values. These models have important limitations, including reliance on a limited array of laboratory tests, and use of dichotomous ("high-low") cutoffs. We applied a Laboratory-Wide Association Study (LWAS) framework to systematically evaluate common clinical laboratory results associated with survival for patients diagnosed with mRCC.

methodsWe used laboratory data for 3,385 patients diagnosed with mRCC from 2002 to 2017. We developed a LWAS framework, to examine the association with 53 common clinical laboratory tests results (641,712 measurements) and overall survival. We employed false-discovery rate to test the association of multiple laboratory tests with survival, and validated these results using 3 separate cohorts to generate a standardized hazard ratio (sHR), reported for a 1 standard deviation unit change in each laboratory test.

resultsThe LWAS approach confirmed the association of laboratory values currently used in prognostic models with survival, including calcium (HR 1.35, 95%CI 1.24-1.48), leukocyte count (HR 1.40, 95%CI 1.30-1.51), platelet count (HR 1.36, 95%CI 1.27-1.51), and hemoglobin (HR 0.79, 95%CI 0.72-0.86). Use of these tests as continuous variables improved model performance. LWAS also identified acute phase reactants associated with survival not typically included in prognostic models, including serum albumin (HR 0.66, 95%CI 0.61-0.72), ferritin (HR 1.25, 95%CI 1.08-1.45), alkaline phosphatase (HR 1.31, 95%CI 1.23-1.40), and C-reactive protein (HR 1.70, 95%CI 1.14-2.53).

conclusionsRoutinely measured laboratory tests can refine current prognostic models, facilitate comparisons across clinical trial cohorts, and match patients with specific systemic therapies.

Indexed as

AgedCarcinoma, Renal CellCohort StudiesFemaleHematologic TestsHumansKidney NeoplasmsLaboratories, ClinicalMaleMiddle AgedPrognosisSurvival RateEWASLaboratory testsMetastaticPrognosisRenal cell carcinoma

Identifiers

PMID34580027
PMCPMC10313329
OpenAlexW3203378808

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.