Factors impacting survival of patients with post-surgical disease recurrence in non-small cell lung cancer (NSCLC)
Bibliographic record
Abstract
7223 Background: There are no standard recommendations for follow-up of NSCLC patients post surgery. To be of value, follow-up should detect disease recurrence early enough to allow timely initiation of effective treatment leading to clinical benefit. Methods: Patients diagnosed with NSCLC in Manitoba, Canada, who underwent a surgical procedure at the two teaching hospitals between January 1996 and December 2001, were identified using the Cancer Registry. We included 435 patients who underwent complete surgical resection of pathologic Stage IA to IIB disease. To date, a detailed retrospective chart review has been completed on 249 of these patients. Median follow-up of this population was 3.45 years. Results: The median age was 66.4 years and 51% were male. 68% had Stage I disease. Lobectomy (73%) was more commonly performed over wedge resection (14%) and pneumonectomy (13%). The most frequent histological diagnosis was adenocarcinoma (52%) followed by squamous cell (29%) and bronchoalveolar carcinoma (13%). Disease recurred in 68% of patients. Recurrence was detected in 52 patients by routine imaging during follow-up. 117 had symptoms suggestive of disease recurrence prompting additional investigation. Median time to recurrence was 1.2 and 1.5 years (NS) respectively for the symptomatic and asymptomatic group. The median overall survival of the asymptomatic patients (4.19 years) was significantly (p = 0.007) greater than the symptomatic patients (2.66 years). Similarly, the median survival from the time of recurrence was greater for the asymptomatic patients (1.6 vs. 0.7 years, p = 0.004). A multivariate analysis identified symptoms (p = 0.02) at the time of recurrence and stage (p = 0.01) of the disease at the initial presentation as significant independent factors impacting overall survival. Only the absence of symptoms had a significant association (p = 0.006) with improved survival after diagnosis of recurrent disease. Conclusions: The diagnosis of recurrence while patients are asymptomatic resulted in better survival. This may suggest that routine post-surgical follow-up of patients with early NSCLC is justified. No significant financial relationships to disclose.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".