Smoking Habit and Respiratory Function Predict Patients' Outcome after Surgery for Lung Cancer, Irrespective of Histotype and Disease Stage.

NSCLC data mining personalized medicine predictors thoracic surgery

Journal

Journal of clinical medicine
ISSN: 2077-0383
Titre abrégé: J Clin Med
Pays: Switzerland
ID NLM: 101606588

Informations de publication

Date de publication:
16 Feb 2023
Historique:
received: 29 01 2023
revised: 05 02 2023
accepted: 13 02 2023
entrez: 25 2 2023
pubmed: 26 2 2023
medline: 26 2 2023
Statut: epublish

Résumé

Growing evidence suggests that sublobar resections offer more favorable outcomes than lobectomy in early-stage lung cancer surgery. However, a percentage of cases that cannot be ignored develops disease recurrence irrespective of the surgery performed with curative intent. The goal of this work is thus to compare different surgical approaches, namely, lobectomy and segmentectomy (typical and atypical) to derive prognostic and predictive markers. Here we analyzed a cohort of 153 NSCLC patients in clinical stage TNM I who underwent pulmonary resection surgery with a mediastinal hilar lymphadenectomy from January 2017 to December 2021, with an average follow-up of 25.5 months. Partition analysis was also applied to the dataset to detect outcome predictors. The results of this work showed similar OS between lobectomy and typical and atypical segmentectomy for patients with stage I NSCLC. In contrast, lobectomy was associated with a significant improvement in DFS compared with typical segmentectomy in stage IA, while in stage IB and overall, the two treatments were similar. Atypical segmentectomy showed the worst performance, especially in 3-year DFS. Quite unexpectedly, outcome predictor ranking analysis suggests a prominent role of smoking habits and respiratory function, irrespective of the tumor histotype and the patient's gender. Although the limited follow-up interval cannot allow conclusive remarks about prognosis, the results of this study suggest that both lung volumes and the degree of emphysema-related parenchymal damage are the strongest predictors of poor survival in lung cancer patients. Overall, these data point out that greater attention should be addressed to the therapeutic intervention for co-existing respiratory diseases to obtain optimal control of early lung cancer.

Sections du résumé

BACKGROUND BACKGROUND
Growing evidence suggests that sublobar resections offer more favorable outcomes than lobectomy in early-stage lung cancer surgery. However, a percentage of cases that cannot be ignored develops disease recurrence irrespective of the surgery performed with curative intent. The goal of this work is thus to compare different surgical approaches, namely, lobectomy and segmentectomy (typical and atypical) to derive prognostic and predictive markers.
PATIENTS AND METHODS METHODS
Here we analyzed a cohort of 153 NSCLC patients in clinical stage TNM I who underwent pulmonary resection surgery with a mediastinal hilar lymphadenectomy from January 2017 to December 2021, with an average follow-up of 25.5 months. Partition analysis was also applied to the dataset to detect outcome predictors.
RESULTS RESULTS
The results of this work showed similar OS between lobectomy and typical and atypical segmentectomy for patients with stage I NSCLC. In contrast, lobectomy was associated with a significant improvement in DFS compared with typical segmentectomy in stage IA, while in stage IB and overall, the two treatments were similar. Atypical segmentectomy showed the worst performance, especially in 3-year DFS. Quite unexpectedly, outcome predictor ranking analysis suggests a prominent role of smoking habits and respiratory function, irrespective of the tumor histotype and the patient's gender.
CONCLUSIONS CONCLUSIONS
Although the limited follow-up interval cannot allow conclusive remarks about prognosis, the results of this study suggest that both lung volumes and the degree of emphysema-related parenchymal damage are the strongest predictors of poor survival in lung cancer patients. Overall, these data point out that greater attention should be addressed to the therapeutic intervention for co-existing respiratory diseases to obtain optimal control of early lung cancer.

Identifiants

pubmed: 36836096
pii: jcm12041561
doi: 10.3390/jcm12041561
pmc: PMC9967492
pii:
doi:

Types de publication

Journal Article

Langues

eng

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Auteurs

Davide Piloni (D)

Cardiothoracic and Vasculat Department, Unit of Respiratory Diseases, IRCCS Policlinico San Matteo, 27100 Pavia, Italy.

Francesco R Bertuccio (FR)

Cardiothoracic and Vasculat Department, Unit of Respiratory Diseases, IRCCS Policlinico San Matteo, 27100 Pavia, Italy.
Medical School, University of Pavia, 27100 Pavia, Italy.

Cristiano Primiceri (C)

Cardiothoracic and Vascular Department, Unit of Thoracic Surgery, IRCCS Policlinico San Matteo, 27100 Pavia, Italy.

Pietro Rinaldi (P)

Cardiothoracic and Vascular Department, Unit of Thoracic Surgery, IRCCS Policlinico San Matteo, 27100 Pavia, Italy.

Vittorio Chino (V)

Cardiothoracic and Vasculat Department, Unit of Respiratory Diseases, IRCCS Policlinico San Matteo, 27100 Pavia, Italy.
Medical School, University of Pavia, 27100 Pavia, Italy.

David Michael Abbott (DM)

Department of Surgical, Pediatric and Diagnostic Sciences, University of Pavia, 19001 Pavia, Italy.

Federico Sottotetti (F)

Department of Medical Oncology, IRCCS ICS Maugeri, 27100 Pavia, Italy.

Chandra Bortolotto (C)

Department of Surgical, Pediatric and Diagnostic Sciences, University of Pavia, 19001 Pavia, Italy.
Department of Diagnostic Services and Imaging, Unit of Radiology, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy.

Francesco Agustoni (F)

Department of Internal Medicine and Medical Therapeutics, University of Pavia Medical School, 27100 Pavia, Italy.
Department of Oncology, Unit of Oncology, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy.

Jessica Saddi (J)

Medical School, Milano-Bicocca of University, 20900 Monza, Italy.
Department of Oncology, Unit of Radiation Therapy, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy.

Giulia M Stella (GM)

Cardiothoracic and Vasculat Department, Unit of Respiratory Diseases, IRCCS Policlinico San Matteo, 27100 Pavia, Italy.
Department of Internal Medicine and Medical Therapeutics, University of Pavia Medical School, 27100 Pavia, Italy.

Classifications MeSH