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The time toxicity efficacy-effectiveness gap: A population-based study of stage III/IV non-small cell lung cancer (NSCLC) in Ontario, Canada.

2024· article· en· W4402985672 on OpenAlexaffabout
Arjun Gupta, Paul Nguyen, Brooke E. Wilson, Christopher M. Booth, Timothy P. Hanna

Bibliographic record

VenueJCO Oncology Practice · 2024
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsQueen's UniversityInstitute for Clinical Evaluative Sciences
Fundersnot available
KeywordsToxicityStage (stratigraphy)OncologyMedicineLung cancerInternal medicinenon-small cell lung cancer (NSCLC)PopulationEnvironmental healthBiology

Abstract

fetched live from OpenAlex

133 Background: While patients enrolled in clinical trials tend to have superior cancer-specific outcomes relative to those in routine practice (the ‘’efficacy-effectiveness gap’’), it is unknown if this gap extends to time toxicity. While trial protocols can impose additional contact days, trial participants also tend to be healthier, perhaps needing fewer contact days. We sought to evaluate the time toxicity efficacy-effectiveness gap among patients with stage III/IV NSCLC. Methods: We created a population-based, retrospective cohort with health administrative data covering the population of Ontario, Canada (15.5 million), of adults aged ≥20 years diagnosed with stage III/IV NSCLC in 2014-2017 and died in 2014-2019, receiving palliative systemic anti-cancer drug(s) as part of a trial. We matched patients 1:1 to those who received the same drug(s) in the real world (post-approval) in the same line of treatment, and received the same total lines of therapy. We calculated contact days (days with healthcare contact outside the home) from diagnosis to death and measured overall survival. We plotted, normalized, and fitted with cubic splines the weekly percentage of contact days to obtain trajectories over the disease course. Results: We identified and matched 55 trial participants to 55 patients in routine practice. Trial participants were younger (median age, 62 vs 66 years), had fewer co-morbidities (hypertension, 35% vs 53%), and more often had de novo metastatic disease (82% vs 67%). Median lines of therapy were 2. Systemic therapy regimens most commonly included immunotherapy (n=41, 75%). Trial participants initiated systemic therapy sooner than in routine practice (median 2.0 vs 2.4 months). Trial participants had a longer overall survival (median 13.8 vs 11.6 months) and a similar number of contact days (median 79 vs 78 days). The percentage of contact days was lower in trial participants due to longer survival (median 19% vs 22%). Trial participants had similar acute/assisted institutional care contact days (median 19 vs 18 days), but more days with laboratory tests (median 23 vs 17 days), systemic therapy (median 9 vs 6 days), and radiotherapy visits (median 15 vs 11 days). Normalized trajectories for both cohorts followed a ‘’U-shape’’; the difference between the maximal peak and trough was smaller in trial participants. Conclusions: We describe a novel efficacy-effectiveness gap in time toxicity, in addition to the previously established efficacy-effectiveness gap in overall survival. Encouragingly, trial participants did not experience delays in treatment, and initiated treatments sooner than in routine practice. Among trial participants, the higher number of contact days for tests, and the shallower U-shaped curve (indicating frequent visits even when relatively well) indicate potential opportunities to decrease trial-related time toxicity.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.024
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.017
GPT teacher head0.363
Teacher spread0.346 · 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 teacher head, 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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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