Pneumonectomy for lung cancer in the elderly: lessons learned from a multicenter study
Bibliographic record
Abstract
Background: 60% of patients diagnosed with lung cancer are older than 65 years and are at risk for substandard treatment due to a reluctance to recommend surgery. Pneumonectomy remains a high risk procedure especially in elderly patients. Nevertheless, the impact of age and neoadjuvant treatment on outcomes after pneumonectomy is still not well described. Methods: We performed a multicentric retrospective study, analyzing outcomes of patients older than 70 years who underwent pneumonectomy for central primary lung malignancy between January 2009 and June 2019 in 7 thoracic surgery departments: Lucerne and Bern (Switzerland), Hamilton (Canada), Alicante (Spain), Monza (Italy), London (UK), Leuven (Belgium). Survival was estimated with Kaplan-Meier, and differences in survival were determined by log-rank analysis. We investigated pre- and post-operative prognostic factors using Cox proportional hazards regression model; multivariable analysis was performed only with variables, which were statistically significant at the invariable analysis. Results: A total of 136 patients were included in the study. Mean age was 73.8 years (SD 3.6). 24 patients (17.6%) had an induction treatment (chemotherapy alone in 15 patients and chemo-radiation in 9). Mean length of stay (LOS) was 12.6 days (SD 10.39) and 74 patients (54.4%) had experienced a post-operative complication: 29 (21.3%) had a pulmonary complication, 33 (24.3%) had a cardiac complication and in 12 cases (8.8%) patients experienced both cardiac and pulmonary complications. 16 patients were readmitted [median LOS 13.7 days (range, 2–39 days)] and of those 14 (10.3%) required redo surgery. Median overall survival (OS) of the entire cohort was 38 months (95% CI: 29.9–46.1 months); in-hospital mortality was 1.5%, 30-day mortality rate was 3.7%, while 90-day mortality was 8.8% accounting for 5 and 12 patients respectively. Patients receiving neo-adjuvant therapy did not experience a higher incidence of postoperative complications (P=0.633), did not have a longer postoperative course (P=0.588), nor did they have an increased mortality rate (P=0.863). Conclusions: Age should not be considered an absolute contraindication for pneumonectomy in elderly patients even after neoadjuvant treatment. It has become apparent that especially in these patients, a patient-tailored approach with a careful selection should be used to define the risk-benefit balance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".