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Treatment outcomes in renal cell carcinoma patients with metastases to the pancreas and other sites.

2021· article· en· W3169355614 on OpenAlexaff
Cassandra Duarte, Benoit Beuselinck, Nicole Weise, Nazlı Dizman, Katharine A. Collier, Haoran Li, Nieves Martínez Chanzá, Roy Elias, Tracy L. Rose, James Brugarolas, Neeraj Agarwal, Amir Mortazavi, Sumanta K. Pal, Rana R. McKay, Junxiao Hu, Elaine T. Lam

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsOccupational Cancer Research Centre
Fundersnot available
KeywordsMedicineRenal cell carcinomaPancreasInternal medicineOncologySystemic therapyNephrectomyCancerGastroenterologyUrologyKidney

Abstract

fetched live from OpenAlex

4557 Background: Metastatic RCC (mRCC) involving the pancreas is distinct from RCC involving other metastatic sites and is characterized by an indolent clinical course, heightened angiogenesis, and an inflamed stroma (PMID: 32271170). We previously reported on outcomes of RCC patients (pts) with pancreatic oligometastasis (ASCO GU 2020). We now report on outcomes in pts with mRCC involving the pancreas in conjunction with other metastases (mets). Methods: We conducted a retrospective, multi-institutional study of mRCC pts with mets to the pancreas and other sites. Data on pt demographics, tumor characteristics, systemic therapy, and outcomes were collected. Pts were classified based on treatment category: immunotherapy (IO) or vascular endothelial growth factor/receptor inhibitors (VEGFI). Outcomes measured included objective response rates (ORR), time-on-treatment (TOT), and overall survival (OS). Results: The analysis included 229 pts from 9 institutions, diagnosed between 1985-2020. Of these, 211 (92%) had clear-cell histology; 131 (57%) had nephrectomy; 41 (18%) had local pancreas-directed therapy; 111 (48%) had synchronous presentation of disease in the pancreas and other sites at time of mets. IMDC risk was favorable in 33%, intermediate in 41%, poor in 11%, and unknown in 15% pts. Median lines of therapy was 2 (range 0-9). Of 219 pts who received first-line (1L) therapy, 151 (69%) had VEGFI therapy, 41 (19%) had IO, and 18 (8%) had VEGFI/IO combination (Table). The IO group included 21 pts on checkpoint inhibitor (CPI), 16 pts on HD-IL2, 4 pts on other IO. 1L ORR was 39.7% for VEGFI (95% CI 31.8-48.0) and 31.7% for IO (95% CI 18.1-48.1) and was not statistically significant (NS, OR 1.4, 95% CI 0.65-3.23, p = 0.371). Median TOT for 1L therapy was 11.6m for VEGFI and 6.5m for IO (p = 0.0106). With a median follow-up of 51.5m, the median OS (mOS) for all pts from time of metastatic disease was 7.7 years (y) (95% CI 6.3-10.3). The mOS for pts who received 1L VEGFI was 7.6y (95% CI 5.5-9.5) and was not reached (NR) for those who got 1L IO (95%CI 6.5-NR); this difference was significant with an unadjusted p-value of 0.029. The pair-wise comparison between mOS of the 1L CPI subgroup compared to that of the 1L VEGFI group was significant (p = 0.0148). Conclusions: Consistent with the literature, mRCC pts with involvement of the pancreas in this study have prolonged OS compared to historical OS for the standard mRCC population. Additionally, our findings suggest that the choice of first-line therapy may impact outcomes. Additional analyses will be presented.[Table: see text]

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.100
GPT teacher head0.399
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations2
Published2021
Admission routes1
Has abstractyes

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