Comparison of predicted postoperative forced expiratory volume in the first second (FEV1) using lung perfusion scintigraphy with observed forced expiratory volume in the first second (FEV1) post lung resection

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

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

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

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

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.

Lung Cancer Management in Low and Middle-Income Countries

Lung cancer is an increasing problem in the developing world due to rising trends in smoking, high incidence of air pollution, lack of awareness and screening, delayed presentation, and diagnosis at the advanced stage. Even after diagnosis, there are disparities in access to health care facilities and inequitable distribution of resources and treatment options. In addition, the shortage of trained personnel and infrastructure adds to the challenges faced by patients with lung cancer in these regions. A multi-pronged effort targeting tobacco cessation, health promotion and awareness, capacity building, and value-based care are the need of the hour.

Complication and lung function impairment prediction using perfusion and computed tomography air trapping (CLIPPCAIR): protocol for the development and validation of a novel multivariable model for the prediction of post-resection lung function

Background

Recent advancements in computed tomography (CT) scanning and post processing have provided new means of assessing factors affecting respiratory function. For lung cancer patients requiring resection, and especially those with respiratory comorbidities such as chronic obstructive pulmonary disease (COPD), the ability to predict post-operative lung function is a crucial step in the lung cancer operability assessment. The primary objective of the CLIPPCAIR study is to use novel CT data to develop and validate an algorithm for the prediction of lung function remaining after pneumectomy/lobectomy.

Methods

Two sequential cohorts of non-small cell lung cancer patients requiring a pre-resection CT scan will be recruited at the Montpellier University Hospital, France: a test population (N=60) on which predictive models will be developed, and a further model validation population (N=100). Enrolment will occur during routine pre-surgical consults and follow-up visits will occur 1 and 6 months after pneumectomy/lobectomy. The primary outcome to be predicted is forced expiratory volume in 1 second (FEV1) six months after lung resection. The baseline CT variables that will be used to develop the primary multivariable regression model are: expiratory to inspiratory ratios of mean lung density (MLD_e/i for the total lung and resected volume), the percentage of voxels attenuating at less than ‒950 HU (PVOX_‒950 for the total lung and resected volume) and the ratio of iodine concentrations for the resected volume over that of the total lung. The correlation between predicted and real values will be compared to (and is expected to improve upon) that of previously published methods. Secondary analyses will include the prediction of transfer factor for carbon monoxide (TLCO) and complications in a similar fashion. The option to explore further variables as predictors of post-resection lung function or complications is kept open.

Discussion

Current methods for estimating post-resection lung function are imperfect and can add assessments (such as scintigraphy) to the pre-surgical workup. By using CT imaging data in a novel fashion, the results of the CLIPPCAIR study may not only improve such estimates, it may also simplify patient pathways.

Trial registration

Clinicaltrials.gov (NCT03885765).