Meta-analysis of Lobectomy and Sublobar Resection for Stage I Non-small Cell Lung Cancer With Spread Through Air Spaces

Spread Through Air Spaces (STAS): Inter-responder Agreement and Comparison between Pulmonary and General Pathologists

Spread through air spaces (STAS), an important prognostic indicator included in the 2015 WHO classification, is defined as micropapillary, solid and/or single tumor cell clusters beyond the edge of the main mass and distinct from processing artifacts. This study aimed to assess inter-responder agreement on current STAS criteria vs artifacts, identify discrepancies, and compare responses between pulmonary and general pathologists. A multiple-choice online questionnaire illustrating multiple criteria for STAS vs artifacts was available internationally for 6 days to Pulmonary Pathology Society members, thoracic pathology course attendees and International Association for the Study of Lung Cancer pathology committee members. Additional four questions gathered demographic and practice setting information. 136 unique responses were analyzed. The majority were from North America and Europe (42.6 and 30.2%), practicing pulmonary pathology (70.6%) in academia (64.7%), and with >20 years of experience (31.6%). Excluding trainees, the greatest overall agreement was in defining solid and micropapillary tumor clusters of STAS located > 3 alveolar spaces from the main tumor edge (91.5%) and recognizing strips of ciliated cells as artifacts (97.7%). Lesser agreement on STAS was evident when tumor cell clusters were immediately adjacent to the tumor edge, a single tumor cell cluster was present at the tissue edge, tumor cell clusters were jagged-edged, or tumor cell clusters were admixed with ciliated cell strips (artifacts). There was no significant difference in agreements on STAS for multiple criteria between pulmonary vs. general pathologists. Significant inter-responder agreement on STAS vs. artifacts was achieved only for a few criteria. To improve reproducibility of STAS vs artifacts, areas of lesser agreement require further clarification.

Association between the triglyceride-glucose index and mortality in critically ill patients: A meta-analysis

BACKGROUND

To further identify the association of the triglyceride-glucose (TyG) index with the risk of mortality among critically ill patients admitted to the intensive care unit (ICU).

METHODS

The PubMed, Web of Science, and EMBASE databases were searched for relevant studies up to February 2, 2024. The primary outcomes were in-hospital mortality and ICU mortality. The secondary outcomes were 30-day mortality, 90-day mortality, and 1-year mortality. The hazard ratios (HRs) with 95% confidence intervals (CIs) were combined to evaluate the associations between the TyG index and the above endpoints. All the statistical analyses were performed with STATA 15.0 software.

RESULTS

Ten studies involving 22,694 patients were included. The pooled results demonstrated that an elevated TyG index indicated an increased risk of in-hospital mortality (HR = 1.76, 95% CI: 1.41-2.18, P < .001), ICU mortality (HR = 1.52, 95% CI: 1.33-1.74, P < .001), 30-day mortality (HR = 1.50, 95% CI: 1.02-2.19, P = .037), 90-day mortality (HR = 1.42, 95% CI: 1.01-2.00, P = .043), and 1-year mortality (HR = 1.19, 95% CI: 1.11-1.28, P < .001). Subgroup analysis for in-hospital mortality and ICU mortality based on sex, age, body mass index and hypertension showed similar results. However, subgroup analysis stratified by diabetes mellitus (DM) revealed that the associations of the TyG index with in-hospital mortality (HR = 2.21, 95% CI: 1.30-3.78, P = .004) and ICU mortality (HR = 1.93, 95% CI: 0.95-3.94, P = .070) were observed only among patients without DM.

CONCLUSION

The TyG index was significantly associated with mortality among critically ill patients without DM, and an elevated TyG index predicted an increased risk of mortality.

The International Association for the Study of Lung Cancer (IASLC) Staging Project for Lung Cancer: Recommendation to Introduce Spread Through Air Spaces as a Histologic Descriptor in the Ninth Edition of the TNM Classification of Lung Cancer. Analysis of 4061 Pathologic Stage I NSCLC

INTRODUCTION

Spread through air spaces (STAS) consists of lung cancer tumor cells that are identified beyond the edge of the main tumor in the surrounding alveolar parenchyma. It has been reported by meta-analyses to be an independent prognostic factor in the major histologic types of lung cancer, but its role in lung cancer staging is not established.

METHODS

To assess the clinical importance of STAS in lung cancer staging, we evaluated 4061 surgically resected pathologic stage I R0 NSCLC collected from around the world in the International Association for the Study of Lung Cancer database. We focused on whether STAS could be a useful additional histologic descriptor to supplement the existing ones of visceral pleural invasion (VPI) and lymphovascular invasion (LVI).

RESULTS

STAS was found in 930 of 4061 of the pathologic stage I NSCLC (22.9%). Patients with tumors exhibiting STAS had a significantly worse recurrence-free and overall survival in both univariate and multivariable analyses involving cohorts consisting of all NSCLC, specific histologic types (adenocarcinoma and other NSCLC), and extent of resection (lobar and sublobar). Interestingly, STAS was independent of VPI in all of these analyses.

CONCLUSIONS

These data support our recommendation to include STAS as a histologic descriptor for the Ninth Edition of the TNM Classification of Lung Cancer. Hopefully, gathering these data in the coming years will facilitate a thorough analysis to better understand the relative impact of STAS, LVI, and VPI on lung cancer staging for the Tenth Edition TNM Stage Classification.

Established the prediction model of early-stage non-small cell lung cancer spread through air spaces (STAS) by radiomics and genomics features

BACKGROUND

This study was aimed to establish a prediction model for spread through air spaces (STAS) in early-stage non-small cell lung cancer based on imaging and genomic features.

METHODS

We retrospectively collected 204 patients (47 STAS+ and 157 STAS-) with non-small cell lung cancer who underwent surgical treatment in the Jinling Hospital from January 2021 to December 2021. Their preoperative CT images, genetic testing data (including next-generation sequencing data from other hospitals), and clinical data were collected. Patients were randomly divided into training and testing cohorts (7:3).

RESULTS

The study included a total of 204 eligible patients. STAS were found in 47 (23.0%) patients, and no STAS were found in 157 (77.0%) patients. The receiver operating characteristic curve showed that radiomics model, clinical genomics model, and mixed model had good predictive performance (area under the curve [AUC] = 0.85; AUC = 0.70; AUC = 0.85).

CONCLUSIONS

The prediction model based on radiomics and genomics features has a good prediction performance for STAS.

Impact of Tumor Size and Differentiation Grade on Survival After Lobectomy and Segmentectomy for Patients with Early-Stage Lung Adenocarcinoma

BACKGROUND

The purpose of this study was to investigate the effect of tumor size and differentiation grade on long term survival in patients with early-stage lung adenocarcinoma (LUAD) after lobectomy and segmentectomy.

PATIENTS AND METHODS

Patients with stage T1-2N0M0 LUAD who underwent lobectomy and segmentectomy were identified from the Surveillance, Epidemiology, and End Results database. Patients were stratified as grade I (well differentiated), grade II (moderately differentiated), and grade III/IV (poorly differentiated/undifferentiated) carcinomas. The effect of tumor size on overall survival (OS) and lung cancer-specific survival (LCSS) was evaluated using the multivariate Cox regression model, including the interaction between tumor size, type of surgery, and tumor differentiation grade. The inverse probability of treatment weighting method was used to adjust for bias between the groups.

RESULTS

A total of 19,857 patients were identified, including 18,759 (94.4%) who underwent lobectomy and 1098 (5.5%) who underwent segmentectomy. A three-way interaction among tumor size, differentiation grade, and type of surgery was observed in the overall cohort. After stratifying by differentiation grade, plots of interaction revealed that lobectomy was associated with improved survival compared with segmentectomy when the tumor size exceeded 23 mm for grade I LUAD and 14 mm for grade II LUAD. No interaction was observed between the studied factors in grade III/IV carcinomas.

CONCLUSIONS

This study interpreted the interaction between tumor size and type of surgery on long-term survival in patients with early stage LUAD and established a tumor size threshold beyond which lobectomy provided survival benefits compared with segmentectomy.

Prognostic Value of the Gustave Roussy Immune Score in Lung Cancer: A Meta-Analysis

PURPOSE

To clarify the prognostic role of the Gustave Roussy immune (GRIm) score in lung cancer.

METHODS

The PubMed, Embase, Web of Science, and China National Knowledge Infrastructure databases were searched up to March 30, 2024. The primary outcomes included overall survival (OS) and progression-free survival (PFS). Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated to evaluate the associations between the GRIm score and survival, and subgroup analyses were performed based on pathological type (non-small cell lung cancer vs. small cell lung cancer), tumor stage (advanced vs. limited stage) and treatment approach (immune checkpoint inhibitor vs. surgery vs. chemotherapy).

RESULTS

Eight studies with 1,333 participants were included. The pooled results showed that a higher GRIm score predicted worse OS (HR = 1.96, 95% CI: 1.54-2.49, P < 0.001) and PFS (HR = 1.64, 95% CI: 1.22-2.21, P = 0.001). Subgroup analyses for OS and PFS showed similar results. However, subgroup analyses for PFS indicated that the association between the GRIm score and PFS was nonsignificant among patients with small cell lung cancer (P = 0.114) and among patients treated with chemotherapy (P = 0.276).

CONCLUSION

The GRIm score might serve as a novel prognostic factor for lung cancer. Additional studies are still needed to verify these findings.

Predictive role of Naples prognostic score for survival in esophageal cancer: A meta-analysis

BACKGROUND

To further clarify the predictive value of pretreatment Naples prognostic score (NPS), calculating based on the serum albumin concentration, total cholesterol level, neutrophil to lymphocyte ratio (NLR) and lymphocyte-to-monocyte ratio (LMR), among esophageal cancer patients based on available evidence.

METHODS

The PubMed, EMBASE, Web of Science and CNKI databases were searched up to December 1, 2023 for relevant studies. Overall survival (OS), progression-free survival (PFS) and cancer-specific survival (CSS) were endpoints and the hazard ratio (HR) with 95% confidence interval (CI) was combined to evaluate the predictive role of NPS for survival. Subgroup analysis based on pathological type and treatment were further conducted.

RESULTS

Ten retrospective studies with 2250 cases were included in our analysis. Pooled results demonstrated that higher pretreatment NPS predicted poorer OS (HR = 2.24, 95% CI: 1.57-3.20, P < .001), PFS (HR = 3.03, 95% CI: 1.84-4.98, P < .001) and CSS (HR = 2.90, 95% CI: 1.80-4.68, P < .001). Then subgroup analysis for the OS and PFS stratified by the pathological type (squamous cell carcinoma vs esophageal cancer) and treatment (surgery vs non-surgery) were further conducted, which showed similar results.

CONCLUSION

Pretreatment NPS is significantly associated with prognosis in esophageal cancer and higher NPS predicts worse survival among patients with esophageal cancer.

Predictive role of preoperative sarcopenia for long-term survival in rectal cancer patients: A meta-analysis

PURPOSE

To identify the predictive role of sarcopenia in long-term survival among rectal cancer patients who underwent surgery based on available evidence.

METHODS

The Medline, EMBASE and Web of Science databases were searched up to October 20, 2023, for relevant studies. Overall survival (OS), disease-free survival (DFS) and cancer-specific survival (CSS) were the endpoints. Hazard ratios (HRs) and 95% confidence intervals (CIs) were combined to evaluate the association between sarcopenia and survival.

RESULTS

Fifteen studies with 4283 patients were included. The pooled results demonstrated that preoperative sarcopenia significantly predicted poorer OS (HR = 2.07, 95% CI = 1.67-2.57, P<0.001), DFS (HR = 1.85, 95% CI = 1.39-2.48, P<0.001) and CSS (HR = 1.83, 95% CI = 1.31-2.56, P<0.001). Furthermore, subgroup analysis based on neoadjuvant therapy indicated that sarcopenia was a risk factor for worse OS and DFS in patients who received (OS: HR = 2.44, P<0.001; DFS: HR = 2.16, P<0.001) but not in those who did not receive (OS: HR = 2.44, P<0.001; DDFS: HR = 1.86, P = 0.002) neoadjuvant chemoradiotherapy. In addition, subgroup analysis based on sample size and ethnicity showed similar results.

CONCLUSION

Preoperative sarcopenia is significantly related to poor survival in surgical rectal cancer patients and could serve as a novel and valuable predictor of long-term prognosis in these patients.

Association between the geriatric nutritional risk index and clinical outcomes among peritoneal dialysis patients: A meta-analysis

BACKGROUND

To identify the relationship between the geriatric nutritional risk index (GNRI) and clinical outcomes in patients receiving peritoneal dialysis (PD).

METHODS

The PubMed, EBASE, Web of Science and CNKI databases were searched for available studies up to December 25, 2023. The primary outcome was all-cause mortality, and the secondary outcomes included the incidence of PD dropout, major adverse cardiac and cerebrovascular events (MACCEs), technique failure and peritonitis. Hazard ratios (HRs) and 95% confidence intervals (CIs) were combined to evaluate the predictive value of the GNRI for the occurrence of the above endpoints.

RESULTS

Ten cohort studies with 3897 patients were included. The pooled results demonstrated that a lower GNRI was significantly associated with a greater incidence of all-cause mortality (HR = 0.71, 95% CI: 0.55-0.91; P = .007). In addition, a decreased GNRI predicted the occurrence of dropout from PD (HR = 0.971, 95% CI: 0.945-0.998, P = .034) and MACCE (HR = 0.95, 95% CI: 0.92-0.98, P = .001). However, no significant associations of the GNRI with technique failure (P = .167) or peritonitis (P = .96) were observed.

CONCLUSION

A low GNRI is significantly associated with poor clinical outcomes and might serve as a novel and valuable prognostic indicator among PD patients.

Geriatric nutritional risk index predicts postoperative prognosis in older patients with hip fracture: A meta-analysis

BACKGROUND

Hip fracture is common in elderly individuals and is accompanied by a relatively high mortality rate. However, it is currently difficult to accurately predict postoperative prognosis for older patients with hip fractures. The aim of this meta-analysis was to further determine the prognostic value of the geriatric nutritional risk index (GNRI) for patients who underwent hip fracture surgery.

METHODS

The Medline, EMBASE, Web of Science, and CNKI databases were searched up to September 19, 2023, for available studies. The primary and secondary outcomes were the mortality and complication rates, respectively. Hazard ratios (HRs) and relative risks with corresponding 95% confidence intervals (CIs) were separately combined to assess the associations between the GNRI and mortality and complication rates. All the statistical analyses were performed with STATA 15.0 and SPSS 22.0 software.

RESULTS

A total of 9 studies with 3959 patients were included. The pooled results demonstrated that a lower GNRI was significantly related to an increased risk of postoperative mortality (HR = 0.82, 95% CI = 0.72-0.92, P = .001). In addition, the GNRI predicted the risk of overall postoperative complications (52% vs 35.5%, P = .04) and pneumonia (33.3% vs 13.6%, P = .010).

CONCLUSION

The GNRI might serve as a novel prognostic indicator for older patients with hip fractures, and a lower GNRI indicates an increased risk of postoperative mortality and complication rates.

Preoperative nomogram for predicting spread through air spaces in clinical-stage IA non-small cell lung cancer using 18F-fluorodeoxyglucose positron emission tomography/computed tomography

PURPOSE

This study aims to assess the predictive value of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) radiological features and the maximum standardized uptake value (SUVmax) in determining the presence of spread through air spaces (STAS) in clinical-stage IA non-small cell lung cancer (NSCLC).

METHODS

A retrospective analysis was conducted on 180 cases of NSCLC with postoperative pathological assessment of STAS status, spanning from September 2019 to September 2023. Of these, 116 cases from hospital one comprised the training set, while 64 cases from hospital two formed the testing set. The clinical information, tumor SUVmax, and 13 related CT features were analyzed. Subgroup analysis was carried out based on tumor density type. In the training set, univariable and multivariable logistic regression analyses were employed to identify the most significant variables. A multivariable logistic regression model was constructed and the corresponding nomogram was developed to predict STAS in NSCLC, and its diagnostic efficacy was evaluated in the testing set.

RESULTS

SUVmax, consolidation-to-tumor ratio (CTR), and lobulation sign emerged as the best combination of variables for predicting STAS in NSCLC. Among these, SUVmax and CTR were identified as independent predictors for STAS prediction. The constructed prediction model demonstrated area under the curve (AUC) values of 0.796 and 0.821 in the training and testing sets, respectively. Subgroup analysis revealed a 2.69 times higher STAS-positive rate in solid nodules compared to part-solid nodules. SUVmax was an independent predictor for predicting STAS in solid nodular NSCLC, while CTR and an emphysema background were independent predictors for STAS in part-solid nodular NSCLC.

CONCLUSION

Our nomogram based on preoperative 18F-FDG PET/CT radiological features and SUVmax effectively predicts STAS status in clinical-stage IA NSCLC. Furthermore, our study highlights that metabolic parameters and CT variables associated with STAS differ between solid and part-solid nodular NSCLC.

CT-Based Intratumoral and Peritumoral Radiomics Nomograms for the Preoperative Prediction of Spread Through Air Spaces in Clinical Stage IA Non-small Cell Lung Cancer

The study aims to investigate the value of intratumoral and peritumoral radiomics and clinical-radiological features for predicting spread through air spaces (STAS) in patients with clinical stage IA non-small cell lung cancer (NSCLC). A total of 336 NSCLC patients from our hospital were randomly divided into the training cohort (n = 236) and the internal validation cohort (n = 100) at a ratio of 7:3, and 69 patients from the other two external hospitals were collected as the external validation cohort. Univariate and multivariate analyses were used to select clinical-radiological features and construct a clinical model. The GTV, PTV5, PTV10, PTV15, PTV20, GPTV5, GPTV10, GPTV15, and GPTV20 models were constructed based on intratumoral and peritumoral (5 mm, 10 mm, 15 mm, 20 mm) radiomics features. Additionally, the radscore of the optimal radiomics model and clinical-radiological predictors were used to construct a combined model and plot a nomogram. Lastly, the ROC curve and AUC value were used to evaluate the diagnostic performance of the model. Tumor density type (OR = 6.738) and distal ribbon sign (OR = 5.141) were independent risk factors for the occurrence of STAS. The GPTV10 model outperformed the other radiomics models, and its AUC values were 0.887, 0.876, and 0.868 in the three cohorts. The AUC values of the combined model constructed based on GPTV10 radscore and clinical-radiological predictors were 0.901, 0.875, and 0.878. DeLong test results revealed that the combined model was superior to the clinical model in the three cohorts. The nomogram based on GPTV10 radscore and clinical-radiological features exhibited high predictive efficiency for STAS status in NSCLC.

Development and validation of a clinic-radiological model to predict tumor spread through air spaces in stage I lung adenocarcinoma

OBJECTIVES

Tumor spread through air spaces (STAS) is associated with poor prognosis and impacts surgical options. We aimed to develop a user-friendly model based on 2-[18F] FDG PET/CT to predict STAS in stage I lung adenocarcinoma (LAC).

MATERIALS AND METHODS

A total of 466 stage I LAC patients who underwent 2-[18F] FDG PET/CT examination and resection surgery were retrospectively enrolled. They were split into a training cohort (n = 232, 20.3% STAS-positive), a validation cohort (n = 122, 27.0% STAS-positive), and a test cohort (n = 112, 29.5% STAS-positive) according to chronological order. Some commonly used clinical data, visualized CT features, and SUVmax were analyzed to identify independent predictors of STAS. A prediction model was built using the independent predictors and validated using the three chronologically separated cohorts. Model performance was assessed using ROC curves and calculations of AUC.

RESULTS

The differences in age (P = 0.009), lesion density subtype (P < 0.001), spiculation sign (P < 0.001), bronchus truncation sign (P = 0.001), and SUVmax (P < 0.001) between the positive and negative groups were statistically significant. Age ≥ 56 years [OR(95%CI):3.310(1.150-9.530), P = 0.027], lesion density subtype (P = 0.004) and SUVmax ≥ 2.5 g/ml [OR(95%CI):3.268(1.021-1.356), P = 0.005] were the independent factors predicting STAS. Logistic regression was used to build the A-D-S (Age-Density-SUVmax) prediction model, and the AUCs were 0.808, 0.786 and 0.806 in the training, validation, and test cohorts, respectively.

CONCLUSIONS

STAS was more likely to occur in older patients, in solid lesions and higher SUVmax in stage I LAC. The PET/CT-based A-D-S prediction model is easy to use and has a high level of reliability in diagnosing.

Updates on lung adenocarcinoma: invasive size, grading and STAS

Advancements in the classification of lung adenocarcinoma have resulted in significant changes in pathological reporting. The eighth edition of the tumour-node-metastasis (TNM) staging guidelines calls for the use of invasive size in staging in place of total tumour size. This shift improves prognostic stratification and requires a more nuanced approach to tumour measurements in challenging situations. Similarly, the adoption of new grading criteria based on the predominant and highest-grade pattern proposed by the International Association for the Study of Lung Cancer (IASLC) shows improved prognostication, and therefore clinical utility, relative to previous grading systems. Spread through airspaces (STAS) is a form of tumour invasion involving tumour cells spreading through the airspaces, which has been highly researched in recent years. This review discusses updates in pathological T staging, adenocarcinoma grading and STAS and illustrates the utility and limitations of current concepts in lung adenocarcinoma.

Prognostic Role of Pretreatment Prognostic Nutritional Index in Advanced Lung Cancer Patients Receiving First-Line Immunotherapy: A Meta-Analysis

The aim of this study was to further explore the association between pretreatment prognostic nutritional index (PNI) and survival among advanced lung cancer patients who received the first-line immunotherapy based on current relevant studies. Several databases were searched up to July 17, 2023. Progression-free survival (PFS) and overall survival (OS) were primary outcomes and the hazard ratios (HRs) with 95% confidence intervals (CIs) were combined. Subgroup analysis based on the pathological type [non-small cell lung cancer (NSCLC) vs small cell lung cancer (SCLC)] and combination of other therapies (yes vs no) were performed. Ten studies with 1291 patients were included eventually. The pooled results demonstrated that higher pretreatment PNI was significantly related to improved PFS (HR=0.62, 95% CI: 0.48-0.80, P＜0.001) and OS (HR=0.52, 95% CI: 0.37-0.73, P＜0.001). Subgroup analysis revealed that the predictive role of pretreatment PNI for PFS (HR=0.61, 95% CI: 0.45-0.81, P=0.001) and OS (HR=0.52, 95% CI: 0.35-0.77, P=0.001) was only observed among NSCLC patients and the combination of other therapies did not cause an impact on the prognostic role of PNI in lung cancer. Pretreatment PNI was significantly associated with prognosis in advanced NSCLC receiving first-line immunotherapy and patients with a lower pretreatment PNI had poorer survival.

Association between MTHFR gene C677T polymorphism and gestational diabetes mellitus in Chinese population: a meta-analysis

Background and purpose

The relationship of the methylenetetrahydrofolate reductase (MTHFR) gene C677T polymorphism with the incidence of gestational diabetes mellitus (GDM) in the Chinese population remains controversial. This study aimed to further clarify the effect of the MTHFR gene C677T polymorphism on GDM risk among Chinese pregnant women based on current evidence.

Methods

Several databases were searched up to July 29, 2023 for relevant case-control studies. The numbers of patients with and without the T allele of the MTHFR gene C677T polymorphism in the GDM and control groups were determined, and all statistical analyses were performed by RevMan 5.3 software and STATA 15.0 software. Trial sequential analysis (TSA) was performed by TSA version 0.9 beta software to determine the required information size.

Results

A total of 17 case-control studies involving 12345 Chinese participants were included. The pooled results demonstrated that the T allele of the MTHFR gene C677T polymorphism was significantly associated with an increased risk of GDM, which was manifested by the five gene models of the MTHFR C677T polymorphism [T vs. C: odds ratio (OR)=1.59, P=0.03; TT vs. CC: OR=2.24, P<0.001; TC vs. CC: OR=1.28, P=0.05; (TT+TC) vs. CC: OR=1.55, P=0.003; TT vs. (TC+CC): OR=1.89, P<0.001]. Subgroup analysis based on the regions indicated that the significant relationship between the T allele of the MTHFR gene C677T polymorphism and an increased risk of GDM was detected only among the southern population [T vs. C: OR=1.62, P=0.09; TT vs. CC: OR=2.22, P=0.004; TC vs. CC: OR=1.17, P=0.28; (TT+TC) vs. CC: OR=1.43, P=0.03; TT vs. (TC+CC): OR=1.97, P=0.006]. TSA plots showed that the information sizes for the association between the MTHFR gene C677T polymorphism and GDM risk were sufficient in the homozygote (TT vs. CC) and recessive (TT vs. TC+CC) models.

Conclusion

The MTHFR gene C677T polymorphism is closely related to susceptibility to GDM in the southern Chinese population, and the C-T mutation serves as an important genetic risk factor for GDM. More well-designed large case-control studies are needed to further confirm the above findings.

The value of frozen section diagnosis of tumor spread through air spaces in small-sized (≤ 2 cm) non-small cell lung cancer

BACKGROUND

The current accuracy of frozen section diagnosis of tumor spread through air spaces (STAS) in non-small cell lung cancer (NSCLC) is poor. However, the accuracy and prognostic value of STAS assessment on frozen sections in small-sized NSCLC (diameter ≤ 2 cm) is unknown.

METHODS

Three hundred fifty-two patients with clinical stage I NSCLC (≤ 2 cm) were included, of which the paraffin sections and frozen sections were reviewed. The accuracy of STAS diagnosis in frozen sections was assessed using paraffin sections as the gold standard. The relationship between STAS on frozen sections and prognosis was assessed by the Kaplan-Meier method and log-rank tests.

RESULTS

STAS on frozen sections in 58 of 352 patients could not be evaluated. In the other 294 patients, 36.39% (107/294) was STAS-positive on paraffin sections and 29.59% (87/294) on frozen sections. The accuracy of frozen section diagnosis of STAS was 74.14% (218/294), sensitivity was 55.14% (59/107), specificity was 85.02% (159/187) and agreement was moderate (K = 0.418). In subgroup analysis, the Kappa values for frozen section diagnosis of STAS in the consolidation-to-tumor ratio (CTR) ≤ 0.5 group and CTR > 0.5 group were 0.368, 0.415, respectively. In survival analysis, STAS-positive frozen sections were associated with worse recurrence-free survival in the CTR > 0.5 group (P < 0.05).

CONCLUSIONS

The moderate accuracy and prognostic significance of frozen section diagnosis of STAS in clinical stage I NSCLC (≤ 2 cm in diameter; CTR > 0.5) suggests that frozen section assessment of STAS can be applied to the treatment strategy of small-sized NSCLC with CTR > 0.5.

Does the presence of a micropapillary component predict worse prognosis in pathological stage IA lung adenocarcinoma?

Considerable evidence has verified that the micropapillary pattern is significantly associated with worse prognosis in pulmonary adenocarcinoma. However, whether the presence of a micropapillary component in pathological stage IA lung adenocarcinoma is also related to worse prognosis remains unclear up to now. The aim of this meta-analysis was to identify the prognostic role of presence of a micropapillary component in pathological stage IA lung adenocarcinoma patients. Relevant studies were searched from the PubMed, EMBASE, Web of Science and CNKI databases and reviewed. The primary and secondary outcomes were the recurrence risk and long-term survival including the overall survival (OS) and disease-free survival (DFS), respectively. All statistical analysis were conducted by STATA 12.0 software. A total of 5257 lung adenocarcinoma patients at the pathological stage IA from ten retrospective studies were enrolled. The recurrence rates in pathological stage IA lung adenocarcinoma patients with and without the a micropapillary component were 32% [95% confidence interval (CI): 20%- 44%] and 7% (95% CI: 4%-10%) separately and pooled results indicated that presence of a micropapillary component was an obvious risk factor for recurrence [odds ratio (OR)= 3.41, 95% CI: 2.80-4.16, P＜0.001]. Besides, the presence of a micropapillary component was significantly related to poorer OS [hazard ratio (HR)= 2.44, 95% CI: 1.28-4.68, P = 0.007] and DFS (HR=2.60, 95% CI: 1.63-4.16, P＜0.001). Subgroup analysis focusing on invasive adenocarcinoma manifested consistent results. In pathological stage IA lung adenocarcinoma, the presence of a micropapillary component predicts obviously higher recurrence risk and worse prognosis even after focusing on invasive adenocarcinoma. However, more prospective high-quality studies are still needed to verify our findings.

Subsegmentectomy versus segmentectomy resection for the treatment of operable patients with stage IA non-small cell lung cancer: A meta-analysis

Background

There were new points of interest in performing subsegmentectomy and segmentectomy for patients with early stage non-small cell lung cancer (NSCLC). However, whether patients who underwent subsegmentectomy could obtain satisfactory clinical outcomes remains unclear. The present study aimed to compare the clinical outcomes and security of surgical procedures between subsegmentectomy and segmentectomy.

Methods

A systematic review and meta-analysis was performed through five online databases to identify the included literatures which presented intact clinical outcome data among different surgical procedures. The included studies were evaluated based on precise and predefined inclusion criteria.

Results

There were 4 published studies identified in this meta-analysis. A total of 325 patients who underwent subsegmentectomy and 904 patients who underwent segmentectomy were involved in this analysis. The duration of drainage [MD -0.19; 95%CI (-0.36, -0.02), p = 0.03] and postoperative hospital stay [MD -0.30; 95%CI (-0.58, -0.02), p = 0.009] of subsegmentectomy were significantly less than that of segmentectomy. There was no statistically significant difference among recurrence rate [OR 0.85; 95%CI (0.21, 3.42), p = 0.82], operation time, blood loss, incidence of complications [OR 0.83; 95%CI (0.58, 1.20), p = 0.33] between subsegmentectomy and segmentectomy in patients with stage IA NSCLC.

Conclusion

The meta-analysis was firstly performed to compare perioperative outcomes among surgical procedures. The perioperative outcomes were comparable between subsegmentectomy and segmentectomy. Subsegmentectomy might be an alternative treatment for the deep tumor with size less than 1.5 cm and mainly composed of Ground Glass Opacity (GGO).

Bioinformatics algorithm for lung adenocarcinoma based on macropinocytosis-related long noncoding RNAs as a reliable indicator for predicting survival outcomes and selecting suitable anti-tumor drugs

As a highly conserved endocytic mechanism during evolution, macropinocytosis is enhanced in several malignant tumors, which promotes tumor growth by ingesting extracellular nutrients. Recent research has emphasized the crucial role of macropinocytosis in tumor immunity. In the present study, we established a new macropinocytosis-related algorithm comprising molecular subtypes and a prognostic signature, in which patients with lung adenocarcinoma (LUAD) were classified into different clusters and risk groups based on the expression of 16 macropinocytosis-related long noncoding RNAs. According to the molecular subtypes, we discovered that patients with LUAD in cluster1 had a higher content of stromal cells and immune cells, stronger intensity of immune activities, higher expression of PD1, PDL1, and HAVCR2, and a higher tumor mutational burden, while patients in cluster2 exhibited better survival advantages. Furthermore, the constructed prognostic signature revealed that low-risk patients showed better survival outcomes, earlier tumor stage, higher abundance of stromal cells and immune cells, higher immune activities, higher expression of PD1, PDL1, CTLA4, and HAVCR2, and more sensitivity to Paclitaxel and Erlotinib. By contrast, patients with high scores were more suitable for Gefitinib treatment. In conclusion, the novel algorithm that divided patients with LUAD into different groups according to their clusters and risk groups, which could provide theoretical support for predicting their survival outcomes and selecting drugs for chemotherapy, targeted therapy, and immunotherapy.