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Record W3161195108 · doi:10.1016/j.ejca.2021.04.004

Outcomes of patients with solid tumour malignancies treated with first-line immuno-oncology agents who do not meet eligibility criteria for clinical trials

2021· article· en· W3161195108 on OpenAlexaffabout
Chun Loo Gan, Igor Stukalin, Daniel E. Meyers, Shaan Dudani, Heidi A.I. Grosjean, Samantha Dolter, Benjamin W. Ewanchuk, Siddhartha Goutam, Michael Sander, J. Connor Wells, Aliyah Pabani, Tina Cheng, Jose Gerard Monzon, Don Morris, Naveen S. Basappa, Sumanta K. Pal, Lori Wood, Frede Donskov, Toni K. Choueiri, Daniel Y.C. Heng

Bibliographic record

VenueEuropean Journal of Cancer · 2021
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsAlberta Health ServicesQueen Elizabeth II Health Sciences CentreUniversity of AlbertaUniversity of Calgary
FundersGenentechEisaiU.S. Department of DefenseExelixisCongressionally Directed Medical Research ProgramsGateway for Cancer ResearchAstellas PharmaAriad PharmaceuticalsBristol-Myers SquibbIpsenNovartisPfizer
KeywordsMedicineOncologyInternal medicineClinical trialClinical OncologyIntensive care medicineCancer

Abstract

fetched live from OpenAlex

BACKGROUND: Immuno-oncology (IO)-based therapies have been approved based on randomised clinical trials, yet a significant proportion of real-world patients are not represented in these trials. We sought to compare the outcomes of trial-ineligible vs. -eligible patients with advanced solid tumours treated with first-line (1L) IO therapy. PATIENTS AND METHODS: Using the International Metastatic Renal Cell Carcinoma (RCC) Database Consortium and the Alberta Immunotherapy Database, patients with advanced RCC, non-small-cell lung cancer (NSCLC) or melanoma treated with 1L PD-(L)1 inhibition-based therapy were included. Trial eligibility was retrospectively determined as per commonly used exclusion criteria. The outcomes of interest were overall survival (OS), overall response rate (ORR), treatment duration (TD) and time to next treatment (TTNT). RESULTS: A total of 395 of 1241 (32%) patients were deemed trial-ineligible. The main reasons for ineligibility based on preselected exclusion criteria were Karnofsky performance status <70%/Eastern Cooperative Oncology Group performance status >1 (40%, 158 of 395), brain metastases (32%, 126 of 395), haemoglobin < 9 g/dL (16%, 63 of 395) and estimated glomerular filtration rate <40 mL/min (15%, 61 of 395). Between the ineligible vs. eligible groups, the median OS, ORR, median TD and median TTNT were 10.2 vs. 39.7 months (p < 0.01), 36% vs. 47% (p < 0.01), 2.7 vs. 6.9 months (p < 0.01) and 6.0 vs. 16.8 months (p < 0.01), respectively. Subgroup analyses showed statistically significant inferior OS, TD and TTNT for trial-ineligible vs. -eligible patients across all tumour types. Adjusted hazard ratios for death in RCC, NSCLC and melanoma were 1.84 (95% confidence interval [CI] 1.22-2.77), 2.21 (95% CI 1.58-3.11) and 1.82 (95% CI 1.21-2.74), respectively.. CONCLUSIONS: Thirty-two percent of real-world patients treated with contemporary 1L IO-based therapies were ineligible for clinical trials. Although one-third of the trial-ineligible patients responded to treatment, the overall trial-ineligible population had inferior outcomes than trial-eligible patients. These data may guide patient counselling and temper expectations of benefit.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.018
Threshold uncertainty score0.647

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.145
GPT teacher head0.451
Teacher spread0.306 · 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

Citations50
Published2021
Admission routes2
Has abstractyes

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