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Overall survival benefits of advances in NSCLC systemic treatments: Younger versus older adults.

2021· article· en· W3200159260 on OpenAlexaff
Bonnie Leung, Aria Shokoohi, Zamzam Al‐Hashami, Sara Moore, Alexandra Pender, Selina K. Wong, Ying Wang, Jonn Wu, Cheryl Ho

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicMultiple and Secondary Primary Cancers
Canadian institutionsOttawa HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineInternal medicineSystemic therapyTolerabilityPerformance statusComorbidityOncologyLog-rank testCancerSurvival analysisAdverse effect

Abstract

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93 Background: Historically, there has been limited systemic therapy options for older adults with cancer attributed to underlying frailty, co-morbidities, poor functional status, and limited social supports. In the past decade, treatment for advanced NSCLC has changed with increasing availability of novel therapeutics associated with improved tolerability and efficacy, such as targeted therapy and immunotherapy. The study goal is to compare the difference in overall survival (OS) between younger adults and older adults with the introduction of novel therapeutic options. Methods: All patients with stage IV NSCLC referred to BC Cancer in 2009, 2011, 2015 and 2017 were included in the study. One-year time points were chosen based on molecular testing implementation and provincial formulary listing: baseline (2009), EGFR testing (2011), ALK testing (2015) and immunotherapy listing (2017). Age was categorized as younger (< 70 years) and older (≥70 years) adults. Baseline demographics, simplified comorbidity score (SCS ≥9 associated with poor prognosis), disease characteristics, and systemic therapy details (agent, duration, line of therapy) were collected retrospectively. Univariate analysis using X2 and Fisher’s exact tests were used to compare age groups. OS was calculated using the Kaplan-Meier method and compared using the log-rank test. Results: 3325 patients with stage IV NSCLC were identified. Baseline characteristics for patients < 70 y; female 51%, non-squamous 62%, ECOG ≥2 50%, SCS ≥9 29% vs patients ≥70 y; female 49%, non-squamous 57%, ECOG ≥2 61%, SCS ≥9 58%. In the four time cohorts 2009/2011/2015/2017, systemic treatment was delivered to < 70 y 44/53/51/52 % vs ≥70 y 23/25/28/30 %. Median OS with BSC for < 70 y 3.1/2.8/2.8/2.5 m vs ≥70 y 3.8/3.3/3.4/3.1 m (p = 0.10). Median OS with systemic treatment for < 70 y 9.0/10.9/13.9/15.5 m (p < 0.001) vs ≥70 y 11.4/11.7/13.9/14.9 m (p < 0.001). Median OS by type of treatment BSC/chemotherapy only/targeted therapy/immunotherapy; < 70 y 2.8/8.9/21.4/20.2 m vs ≥70 y 3.1/10.1/21.5/20.1 m (p < 0.001). Conclusions: In this real-world retrospective review of patients with advanced NSCLC, there was an increased uptake of systemic therapy for both age groups with the introduction of novel therapeutics. Although there was a smaller proportion of older adults who received systemic therapy, those who received treatment had comparable OS to their young counterpart. The benefit of systemic therapy in both age groups was seen across the different types of treatments. This suggests with careful assessment and selection of appropriate candidates, older adults with advanced NSCLC should receive equitable access to systemic therapy.

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 score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.089
GPT teacher head0.440
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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Citations0
Published2021
Admission routes1
Has abstractyes

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