Evidence map›Paper›PMID 40341029›Full record

Trial reportJournal for immunotherapy of cancer2025

Early dynamics of clinical and laboratory parameters predict primary refractory disease in patients with metastatic urothelial carcinoma receiving atezolizumab.

Christopher J Graser, Thomas O McDonald, Paul J Catalano, Guru Sonpavde, Franziska Michor

Abstract readClinical Trial, Phase III
In one paragraph

Trial report in Journal for immunotherapy of cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Christopher J GraserDepartment of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.ORCID http://orcid.org/0009-0003-8552-7767
Thomas O McDonaldDepartment of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.ORCID http://orcid.org/0000-0002-5272-0187
Paul J CatalanoDepartment of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.ORCID http://orcid.org/0000-0002-1105-8852
Guru SonpavdeUniversity of Central Florida, Orlando, Florida, USA michor@jimmy.harvard.edu guru.sonpavde.md@adventhealth.com.ORCID http://orcid.org/0000-0002-1010-9611
Franziska MichorDepartment of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts, USA michor@jimmy.harvard.edu guru.sonpavde.md@adventhealth.com.ORCID http://orcid.org/0000-0003-4869-8842

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn patients with metastatic urothelial carcinoma (mUC) receiving programmed cell death ligand 1 (PD-L1) inhibitors, it is critically important to identify primary refractory patients very early to enable modification of therapy before clinical progression and decline of performance status. We hypothesized that baseline and early-on-treatment (EOT) parameters may help identify patients likely to have primary refractory disease.

methodsWe considered baseline and EOT variables measured up to 5 weeks after initiating therapy in the phase 3 clinical trial IMvigor211, which compared atezolizumab versus chemotherapy, in muC patients who had progressed on platinum-based chemotherapy. We used least absolute shrinkage and selection operator-regularized logistic regression models to predict the risk of primary refractory disease employing clinical and laboratory variables.

results902 patients were evaluable for analysis. Our baseline model achieves an area under the curve (AUC) of 0.730, 0.717 for the atezolizumab group and 0.696 for the chemotherapy group. The AUC increases to 0.848 overall with EOT parameters, 0.871 for the atezolizumab group and 0.788 for the chemotherapy group. The EOT model suggests that 33.7% of patients receiving atezolizumab may benefit from switching to chemotherapy, reducing their risk of primary refractoriness from 67.1% to 51.5%.

conclusionsOur prediction model employs readily available and routinely measured clinical and laboratory factors, such as urine-specific gravity, presence of liver metastases, and total protein and erythrocyte counts. It robustly identifies patients with early primary refractory disease to atezolizumab before clinical progression and may inform therapeutic decisions. Validation in larger independent cohorts and other treatments is required.

Indexed as

Antibodies, Monoclonal, HumanizedCarcinoma, Transitional CellUrologic NeoplasmsAgedFemaleHumansMaleMiddle AgedNeoplasm MetastasisAntibodies, Monoclonal, HumanizedatezolizumabBladder CancerChemotherapyImmune Checkpoint InhibitorImmunotherapy

Identifiers

PMID40341029
PMCPMC12060874

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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.