Clinicopathological and prognostic features of operable non-small cell lung cancer patients with diabetes mellitus

Metabolomic Profiling of Tumor Tissues Unveils Metabolic Shifts in Non-Small Cell Lung Cancer Patients with Concurrent Diabetes Mellitus

A comprehensive understanding of the exact influence of type 2 diabetes mellitus (T2DM) on the metabolic status of non-small cell lung cancer (NSCLC) is still lacking. This study explores metabolic alterations in tumor tissues among patients with coexisting NSCLC and T2DM in comparison with NSCLC patients. A combined approach of clinical analysis and metabolomics was employed, including 20 NSCLC patients and 20 NSCLC+T2DM patients. Targeted metabolomics analysis was performed on tumor tissues using the liquid chromatography-mass spectrometry (LC-MS) approach. A clear segregation was observed between NSCLC+T2DM and matched NSCLC tissue samples in Orthogonal Partial Least Squares Discrimination Analysis (OPLS-DA). Furthermore, the levels of 7 metabolites are found to be significantly different between diabetes/nondiabetes tumor tissue samples. The related pathways included arginine biosynthesis, glutathione metabolism, arginine and proline metabolism, purine metabolism, biotin metabolism, and histidine metabolism. 3-Phenyllactic acid, carnitine-C5, carnitine-C12, and serotonin showed a positive linear correlation with fasting blood glucose levels in NSCLC patients. Uridine, pipecolic acid, cytosine, and fasting blood glucose levels were found to have a negative correlation. Our results suggest that NSCLC patients with concurrent T2DM exhibit distinct metabolic shifts in tumor tissues compared to those of solely NSCLC patients.

Incidence and risk factors of pulmonary complications after lung cancer surgery: A systematic review and meta-analysis

Postoperative pulmonary complications (PPCs) are associated with high mortality rates after lung cancer surgery. Although some studies have discussed the different risk factors for PPCs, the relationship between these factors and their impact on PPCs remains unclear. Hence, this study aimed to systematically summarize the incidence and determine the risk factors for PPCs. We conducted a systematic search of five English and four Chinese databases from their inception to April 1, 2023. A total of 34 articles (8 cohort studies and 26 case-control studies) (n = 31696, 5833 with PPCs) were included in the analysis. The primary outcome was the incidence of PPC. The secondary outcome was the odds ratio (OR) of PPCs based on the identified risk factors calculated by RevMan 5.4. A narrative descriptive summary of the study results was presented when pooling the results or conducting a meta-analysis was not possible. The pooled incidence of PPCs was 18.4 %. This meta-analysis demonstrated that TNM staging (OR 4.29, 95 % CI 2.59-7.13), chronic obstructive pulmonary disease (COPD) (OR 2.47, 95 % CI 1.80-3.40), smoking history (OR 2.37, 95 % CI 1.33-4.21), poor compliance with respiratory rehabilitation (OR 1.64, 95 % CI 1.17-2.30), male sex (OR 1.62, 95 % CI 1.28-2.04), diabetes (OR 1.56, 95 % CI 1.07-2.27), intraoperative bleeding volume (OR 1.44, 95 % CI 1.02-2.04), Eastern Cooperative Oncology Group score (ECOG) > 1 (OR 1.37, 95 % CI 1.04-1.80), history of chemotherapy and/or radiotherapy (OR 1.32, 95 % CI 1.03-1.70), older age (OR 1.18, 95 % CI 1.11-1.24), and duration of surgery (OR 1.07, 95 % CI 1.04-1.10) were significantly associated with a higher risk of PPCs. In contrast, the peak expiratory flow rate (PEF) (OR 0.99, 95 % CI 0.98-0.99) was a protective factor. Clinicians should implement targeted and effective interventions to prevent the occurrence of PPCs.

Long-term survival analysis of patients with stage IIIB-IV non-small cell lung cancer complicated by type 2 diabetes mellitus: A retrospective propensity score matching analysis

BACKGROUND

This study aimed to determine the effect of type 2 diabetes mellitus (T2DM) on overall survival (OS) of patients with stage IIIB-IV non-small cell lung cancer (NSCLC).

METHODS

We retrospectively analyzed patients with stage IIIB-IV NSCLC from January 2015 to December 2018 in the Department of Oncology at the First Affiliated Hospital of Anhui University of Traditional Chinese Medicine. Kaplan-Meier plots, log-rank tests, and Cox proportional hazards regression models were used to describe the effect of T2DM on the OS of patients with stage IIIB-IV NSCLC.

RESULTS

This study collected data on 76 patients with NSCLC and T2DM (group A) and 214 NSCLC patients without T2DM (group B). After propensity score matching (PSM) analysis, 74 patients were included in each group. The mean OS of all patients was 17 months (range, 11-31 months). The mean OS of group A was 15 months (range, 8-25 months) and the mean OS of group B was 20 months (range, 14-39 months). The mean OS of group B was longer than group A, and the difference was statistically significant. Univariate analysis of the clinical data showed that T2DM and complications were significantly correlated with the prognosis of patients with stage IIIB-IV NSCLC (p = 0.003 and p = 0.034). Multivariate Cox model analysis showed that T2DM and complications were independent prognostic factors for patients with stage IIIB-IV NSCLC (p = 0.002 and p = 0.024, respectively).

CONCLUSION

Stage IIIB-IV NSCLC patients without T2DM have an increased OS compared to patients with stage IIIB-IV NSCLE and T2DM.

Novel application of the traditional lipid ratios as strong risk predictors of nonsmall-cell lung cancer risk in a Chinese population

Dyslipidemia has been associated with cancer risk, yet the relationship between lipid ratios and nonsmall-cell lung cancer (NSCLC) is still unclear. This study aimed to explore the value of lipid ratios, including total cholesterol/high-density lipoprotein cholesterol (TC/HDL-C) and triglyceride/HDL-C (TG/HDL-C) as predictors of NSCLC in a Chinese population. Adult patients with histologically confirmed NSCLC, without a previous history of cancer, concomitant disease associated with lipid metabolism disorders, or usage of lipid-lowering drugs, were enrolled from a single center. Controls without NSCLC, matched for age and sex, were enrolled from the same Center. Lipid profile including TC, TG, HDL-C were measured in all participants. TC/HDL-C and TG/HDL-C were calculated based on the levels of TC, TG, HDL-C. Seven hundred eighty-two NSCLC cases and 599 controls were enrolled. NSCLC patients had significantly higher TG/HDL-C and TC/HDL-C levels than those in the control. After controlling for confounding factors, TG/HDL-C (OR = 4.489, 95% CI: 2.463-6.035, P < .001) and TC/HDL-C (OR = 2.396, 95% CI: 2.086-2.752, P = .001) were independently associated with NSCLC risk. The incidence of NSCLC was increased with rising tertiles of TG/HDL-C and TC/HDL-C. Moreover, patients with TNM II-IV stage NSCLC had higher TG/HDL-C and TC/HDL-C than those in TNM I and Tis stage. TG/HDL-C and TC/HDL-C are positively correlated with NSCLC risk and TG/HDL-C is more predictive than TC/HDL-C in predicting the risk of NSCLC. The highest AUC was that of TG/HDL (0.898), at a cutoff point of 0.62, with 83.6% sensitivity and 83.5% specificity.

The Survival Benefit for Optimal Glycemic Control in Advanced Non-Small Cell Lung Cancer Patients With Preexisting Diabetes Mellitus

Background

Diabetes mellitus (DM) is a frequent comorbidity in patients with cancer. This study aimed to evaluate the prognosis of advanced non-small cell lung cancer (NSCLC) patients with DM and to assess whether an optimal glycemic control improves overall survival (OS).

Methods

A total of 1279 advanced NSCLC patients including 300 (23.5%) with preexisting DM were retrospectively reviewed. The continuous relationship between glycated hemoglobin A1C (HbA1c) level and OS was analyzed by restricted cubic spline (RCS) function. Optimal HbA1c cut-off point was determined using X-tile analysis. Survival was analyzed with the Kaplan–Meier method and compared among groups stratified by diabetes status and HbA1c. Multivariable Cox proportional hazards regression analysis was employed to identify prognostic factors for OS after adjusting for baseline characteristics.

Results

DM and non-DM patients had similar OS (median (95% CI): 22.85 (20.05-26.73) vs. 22.22 (20.35-24.76) months, P=0.950). The multivariate Cox regression analyses showed that DM status was not a prognostic factor for OS (HR: 0.952, 95% CI: 0.808-1.122, P=0.559). However, there existed a non-linear but generally positive relationship between the elevated HbA1c level and increased risk of overall mortality. HbA1c > 6.6% was a negative prognostic factor for OS (HR: 1.593, 95% CI: 1.113-2.280, P=0.011). The median OS (95% CI) for nondiabetic patients, DM patients with HbA1c ≤6.6% and those with HbA1c > 6.6% was 22.22 (20.01-24.43), 25.28 (21.79-28.77) and 15.45 (7.57-23.33) months, respectively. Well-controlled DM patients had a comparable crude OS (HR (95% CI): 0.90 (0.76-1.08), P=0.273] compared to nondiabetic patients while patients with HbA1c>6.6% had a worse crude OS than patients without DM (HR (95% CI): 1.70 (1.24-2.34), P=0.001]. The survival benefit of good HbA1c control was prominent in all subgroups.

Conclusion

Impaired glycemic level negatively affects survival for patients with advanced NSCLC while proper glycemic control with HbA1c ≤6.6% improves the OS.