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Elderly patients with unresectable stage 3 NSCLC treated with definitive chemoradiation with or without durvalumab: Safety and outcomes.

2021· article· en· W3170092667 on OpenAlexaff
Malcolm Ryan, Jessica Weiss, Aline Fusco Fares, Ming‐Sound Tsao, Geoffrey Liu, Penelope Ann Bradbury, Natasha B. Leighl, Frances A. Shepherd, Adrian G. Sacher, Sally C. M. Lau

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsUniversity of TorontoUniversity Health NetworkPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineDurvalumabInternal medicinePemetrexedStage (stratigraphy)CohortLung cancerChemotherapyCancerOncologySurgeryCisplatinNivolumab

Abstract

fetched live from OpenAlex

8547 Background: Recently, it has been demonstrated that the addition of durvalumab after chemoradiation (CRT) in unresectable stage 3 non-small cell lung cancer (NSCLC) significantly improves overall survival (OS). The benefit of CRT in elderly patients is considered controversial given its increased toxicity. As such, CRT followed by durvalumab in elderly patients may be underutilized despite its demonstrated superiority. The practice pattern at our center is to offer curative treatment unless clearly contraindicated. We sought to investigate the outcomes of elderly patients treated with CRT +/- durvalumab at our center. Methods: We conducted a review of all stage 3 NSCLC patients treated with CRT between 2018 and 2020. Patients were analyzed based on age: < 70 years, ≥70 years. Endpoints evaluated were treatment patterns, toxicity, progression free survival (PFS) and overall survival (OS). Results: We identified 115 stage 3 patients: 44 patients ≥70 years (70-89) and 71 patients < 70 years (34-69). Patients were fit: ECOG 0-1 (98%/97%), mean Charlson comorbidity index (CCI) (1.1/0.9) in elderly vs young patients; p > 0.05. All other baseline characteristics including PD-L1 expression were similar. The chemotherapy regimens (platinum in combination with etoposide, paclitaxel or pemetrexed), dose intensity (97% vs 97%) and percentage of planned cycles received (91% vs 96%) were similar. There were 2 treatment related deaths from CRT among the younger cohort and none in the elderly patients. At the completion of CRT, 75% of elderly and 72% of young patients received durvalumab. Clinician/patient preference was the most common reason for not receiving consolidation durvalumab in older patients (55% vs 25%). The median time to starting durvalumab was 43 days in the elderly and 37 days in young patients (p = 0.19). Durvalumab was well tolerated in the elderly and incidence of grade ≥3 immune-related adverse events was 9% compared to 6% in young patients; p = 0.68. The durvalumab completion rates were 30% in elderly and 24% in young patients; p = 0.22. Median PFS was similar between elderly and young patients (17.9 vs 10.6 months respectively; p = 0.07), even after adjusting for the CCI (HR 0.60; p = 0.07). The 24- and OS rates are also similar (p = 0.93): 77% in elderly and 77% in young patients. Conclusions: Definitive CRT followed by durvalumab can be safely delivered in elderly patients ≥70 years with comparable outcomes. The non-significant trend towards better PFS in elderly patients suggests that only select fit patients are being referred for treatment. In conclusion, all patients should undergo comprehensive oncologic assessment to determine if curative intent treatment can be delivered to avoid undertreatment of elderly patients.

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)0.001
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.057
GPT teacher head0.407
Teacher spread0.351 · 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
Published2021
Admission routes1
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