Comorbidity and overall survival (OS) in patients with advanced pancreatic cancer (APC): Results from NCIC CTG PA.3-A phase III trial of erlotinib plus gemcitabine (E+G) versus gemcitabine (G) alone.
Bibliographic record
Abstract
4079 Background: The interaction between comorbidity, age and performance status (PS) in patients with APC receiving chemotherapy has yet to be fully explored, but is of clinical importance. A previous analysis of NCIC CTG PA.3 revealed that venous thromboembolism (VTE) as a comorbidity had a negative impact on survival. We further explored comorbidity (aside from VTE), age and PS as predictors of treatment toxicity and outcome in patients receiving G ± E. Methods: Comorbidity was evaluated retrospectively by 2 physicians (independently) using the Charlson Comorbidity Index (CCI), a previously validated measure of comorbidity based on the presence or absence of index medical conditions (VTE not part of index). CCI was correlated with demographic data (age, gender, race), baseline pain intensity, treatment, PS, and OS by chi-square test or Cox model. Results: 569 patients were included; 47% were ≥ 65 years, 34% had comorbidities and 70% had an ECOG PS ≥ 1 at randomization. In univariate analysis of all covariates, higher ECOG PS (PS > 0) was associated with age ≥ 65 yrs (p = 0.009) and age ≥ 65 yrs was associated with CCI > 0 (p = 0.02). When all patients were combined, neither age nor comorbidity was significantly associated with OS. Erlotinib and gemcitabine significantly improved OS compared with gemcitabine alone for patients < 65 yrs of age (adjusted HR 0.73; 95% CI 0.56-0.94; p = 0.01) and those with CCI > 0 (adjusted HR 0.71; 95% CI 0.52-0.97; p = 0.03). Interaction test trended towards significance for age (p = 0.08), but not for comorbidity (p = 0.2) as predictors of OS benefit from the addition of E to G. Toxicity analysis of the E+G group revealed a higher rate of grade ≥ 3 infections in patients ≥ 65 yrs (p = 0.02) and those with CCI > 0 (p = 0.01). Conclusions: Younger age may, but comorbidity does not predict for OS benefit from the addition of erlotinib to gemcitabine. In the E+G group, age and comorbidity were associated with toxicity. Further investigation is required to determine the prognostic/predictive role of comorbidity in the treatment of solid tumors. Refinement of comorbidity indices for specific tumor sites may also be indicated. Author Disclosure Employment or Leadership Position Consultant or Advisory Role Stock Ownership Honoraria Research Funding Expert Testimony Other Remuneration Amgen, UCB Canada
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".