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First-line (1L) immuno-oncology (IO) combination therapies in metastatic renal-cell carcinoma (mRCC): Results from the international mRCC database consortium (IMDC).

2019· article· en· W4232266420 on OpenAlexaff
Shaan Dudani, Jeffrey Graham, Connor Wells, Ziad Bakouny, Sumanta K. Pal, Nazlı Dizman, Frede Donskov, Camillo Porta, Guillermo de Velasco, Aaron R. Hansen, Marco Iafolla, Benoit Beuselinck, Ulka N. Vaishampayan, Lori Wood, Elizabeth Liow, Flora Yan, Takeshi Yuasa, Georg A. Bjarnason, Toni K. Choueiri, Daniel Yick Chin Heng

Bibliographic record

VenueJournal of Clinical Oncology · 2019
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsSunnybrook HospitalDalhousie UniversityPrincess Margaret Cancer CentreUniversity of ManitobaUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsMedicineNivolumabHazard ratioInternal medicineRenal cell carcinomaIpilimumabProportional hazards modelOncologyCohortCancerUrologyGastroenterologyConfidence intervalImmunotherapy

Abstract

fetched live from OpenAlex

4577 Background: In mRCC, ipilimumab and nivolumab (ipi-nivo) is a 1L treatment option. Recent data have also shown efficacy of 1L IO-VEGF (IOVE) inhibitor combinations. Comparative data between these two strategies are limited and the efficacy of subsequent therapies remains unknown. Methods: Using the IMDC dataset, patients (pts) treated with any 1L IOVE combination were compared to those treated with ipi-nivo. Multivariable Cox regression analysis was performed to control for imbalances in IMDC risk factors. Results: 188 pts received 1L IO combination therapy: 113 treated with IOVE combinations and 75 with ipi-nivo. Baseline characteristics and IMDC risk factors were comparable between groups. When comparing IOVE combinations vs ipi-nivo, 1L response rate (RR) was 33% vs 40% (p=0.39), time to treatment failure (TTF) was 14.3 (95% CI 9.2-16.1) vs 10.2 months (95% CI 6.7-15.1, p=0.23), and median overall survival (OS) was not reached (NR) (95% CI 22.3-NR) vs NR (95% CI 35.1-NR, p=0.17). When adjusted for IMDC risk factors, the hazard ratio (HR) for TTF was 0.71 (95% CI 0.46-1.12, p=0.14) and the HR for death was 1.74 (95% CI 0.82-3.68, p=0.14). Second-line (2L) treatments were varied. In pts receiving subsequent VEGF-based therapy, 2L RR was lower in the IOVE (n=20) versus ipi-nivo (n=20) cohort (15% vs 45%; p=0.04), though 2L TTF was not significantly different (3.7 vs 5.4 months, p=0.40, n=55). The use of IO post IOVE was uncommon and 3/5 pts had PD as best response; 2/5 had PR/SD but their 1L IOVE exposure was short at <3 months. Conclusions: There does not appear to be a superior 1L IO combination strategy in mRCC, as lOVE combinations and ipi-nivo have comparable 1L RR, TTF and OS. Most pts received VEGF-based therapy in the 2L. In this group, 2L RR was greater in pts who received ipi-nivo, though there was no difference in 2L TTF. [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)0.003
metaresearch head score (Gemma)0.005
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 score0.007
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.119
GPT teacher head0.407
Teacher spread0.289 · 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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Citations1
Published2019
Admission routes1
Has abstractyes

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