Prognostic stratification model for patients with stage I non-small cell lung cancer adenocarcinoma treated with surgical resection without adjuvant therapies using metabolic features measured on F-18 FDG PET and postoperative pathologic factors

Predictive value of CT and 18F-FDG PET/CT features on spread through air space in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma, a leading cause of cancer-related mortality, demands precise prognostic indicators for effective management. The presence of spread through air space (STAS) indicates adverse tumor behavior. However, comparative differences between 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography(PET)/computed tomography(CT) and CT in predicting STAS in lung adenocarcinoma remain inadequately explored. This retrospective study analyzes preoperative CT and 18F-FDG PET/CT features to predict STAS, aiming to identify key predictive factors and enhance clinical decision-making.

METHODS

Between February 2022 and April 2023, 100 patients (108 lesions) who underwent surgery for clinical lung adenocarcinoma were enrolled. All these patients underwent 18F-FDG PET/CT, thin-section chest CT scan, and pathological biopsy. Univariate and multivariate logistic regression was used to analyze CT and 18F-FDG PET/CT image characteristics. Receiver operating characteristic curve analysis was performed to identify a cut-off value.

RESULTS

Sixty lesions were positive for STAS, and 48 lesions were negative for STAS. The STAS-positive was frequently observed in acinar predominant. However, STAS-negative was frequently observed in minimally invasive adenocarcinoma. Univariable analysis results revealed that CT features (including nodule type, maximum tumor diameter, maximum solid component diameter, consolidation tumor ratio, pleural indentation, lobulation, spiculation) and all 18F-FDG PET/CT characteristics were statistically significant difference in STAS-positive and STAS-negative lesions. And multivariate logistic regression results showed that the maximum tumor diameter and SUVmax were the independent influencing factors of CT and 18F-FDG PET/CT in STAS, respectively. The area under the curve of maximum tumor diameter and SUVmax was 0.68 vs. 0.82. The cut-off value for maximum tumor diameter and SUVmax was 2.35 vs. 5.05 with a sensitivity of 50.0% vs. 68.3% and specificity of 81.2% vs. 87.5%, which showed that SUVmax was superior to the maximum tumor diameter.

CONCLUSION

The radiological features of SUVmax is the best model for predicting STAS in lung adenocarcinoma. These radiological features could predict STAS with excellent specificity but inferior sensitivity.

A novel analytical approach for outcome prediction in newly diagnosed NSCLC based on [18F]FDG PET/CT metabolic parameters, inflammatory markers, and clinical variables

OBJECTIVES

To develop a novel analytical approach based on ¹⁸F-fluorodeoxyglucose ([¹⁸F]FDG) positron emission tomography (PET) metabolic parameters, serum inflammatory markers, and clinical variables to improve the outcome prediction in NSCLC.

METHODS

A total of 190 newly diagnosed NSCLC patients who underwent pretreatment [¹⁸F]FDG PET/CT were retrospectively enrolled and divided into a training cohort (n = 127) and a test cohort (n = 63). Cox regression analysis was used to investigate the predictive values of PET metabolic parameters, inflammation markers, and clinical variables for progression-free survival (PFS) and overall survival (OS). Based on the results of multivariate analysis, PET-based, clinical, and combined models were constructed. The predictive performance of different models was evaluated using time-dependent ROC curve analysis, Harrell concordance index (C-index), calibration curve, and decision curve analysis.

RESULTS

The combined models incorporating SULmax, MTV, NLR, and ECOG PS demonstrated significant prognostic superiority over PET-based models, clinical models, and TNM stage in terms of both PFS (C-index: 0.813 vs. 0.786 vs. 0.776 vs. 0.678, respectively) and OS (C-index: 0.856 vs. 0.792 vs. 0.781 vs. 0.674, respectively) in the training cohort. Similar results were observed in the test cohort for PFS (C-index: 0.808 vs. 0.764 vs. 0.748 vs. 0.679, respectively) and OS (C-index: 0.836 vs. 0.785 vs. 0.726 vs. 0.660, respectively) prediction. The combined model calibrated well in two cohorts. Decision curve analysis supported the clinical utility of the combined model.

CONCLUSIONS

We reported a novel analytical approach combining PET metabolic information with inflammatory biomarker and clinical characteristics, which could significantly improve outcome prediction in newly diagnosed NSCLC.

KEY POINTS

• The nomogram incorporating SULmax, MTV, NLR, and ECOG PS outperformed the TNM stage for outcome prediction in patients with newly diagnosed NSCLC. • The established nomogram could provide refined prognostic stratification.

The prediction of spread through air spaces with preoperative 18F-FDG PET/CT in cases with primary lung adenocarcinoma, its effect on the decision for an adjuvant treatment and its prognostic role

PURPOSE

In lung adenocarcinoma cases, 'spread through air spaces' (STAS) is a new indicator of invasion and directly related to disease survival. The aim of our study is to establish whether a preoperatively performed 18F-Fluorodeoxyglucose (FDG) PET/computed tomography (CT) imaging data can predict the presence of STAS in cases with lung adenocarcinoma and thus predict the decision for the type of surgery and adjuvant chemotherapy.

MATERIALS AND METHODS

Between 2000 and 2019, we retrospectively analyzed 63 patients with lung adenocarcinoma cases that had undergone lobectomy or pneumonectomy. Semiquantitative parameters were calculated and metabolic tumor volume (MTV)/CT volume (CTV) ratio was recorded from FDG PET/CT data. The pathological samples from these patients were evaluated for STAS. All these values were evaluated for their correlation with the alveolar spread.

RESULTS

There was no statistically significant correlation to be found between CTV, MTV, total lesion glycolysis (TLG), standardized uptake value (SUV)max, SUVmean and STAS (P > 0.05). However, MTV/CTV ratio above 1 had statistically more alveolar spread. In the group with an MTV ratio above 1, STAS positivity was 27 (75%), and 9 (25%) did not have STAS, whereas these were 6 (22.2%) patients who had STAS, and 21 (77.8%) did not have STAS in the group with below 1 (P < 0.001).

CONCLUSIONS

In the preoperative PET study inoperable lung adenocarcinoma cases, MTV/CTV ratio higher than 1 was found to predict STAS positivity. As a result, it was found that it provided significant clinical additional information regarding the need for a surgical approach (lobar resection instead of sublobar) and adjuvant chemotherapy.

Undetectable circulating tumor DNA levels correlate with low risk of recurrence/metastasis in postoperative pathologic stage I lung adenocarcinoma patients

OBJECTIVES

The application of circulating tumor DNA (ctDNA) monitoring after resection in pathologic(p) stage I lung adenocarcinoma (LUAD) patients remains controversial and it is of great clinical interest to decipher the difference of genetic features between ground-glass opacity (GGO) and solid nodules (non-GGO) subgroups. We aim to assess the utility of ctDNA in tracking early recurrence or metastasis following surgery and reveal the genetic differences between GGO and non-GGO.

MATERIALS AND METHODS

Tumor tissues and matched postoperative plasma samples were collected from a total of 82 (p)stage I LUAD patients. Comprehensive genomic profiling was performed using capture-based hybrid next generation sequencing by targeting 422 cancer relevant genes.

RESULTS

EGFR and TP53 represent commonly mutated genes in this cohort of (p)stage I lung adenocarcinoma, followed by alterations in ALK, PIK3CA, STK11 and MYC. For a median follow-up period of 22.83 months after surgery, 65 out of 67 ctDNA-negative patients remained progression-free, while 3 out of 15 ctDNA-positive patients progressed [P = 0.040; positive predictive value = 0.20, 95 % confidence interval (CI), 0.04-0.48; negative predictive value = 0.97, 95 % CI, 0.9-1]. With time-dependent Cox regression analysis, we observed that ctDNA positivity significantly correlated with increased probability of early tumor recurrence or metastasis (P = 0.02, HR=8.5). Further comparison between GGO and non-GGO subgroups indicated the frequency of TP53 mutations in non-GGO was markedly higher than that in GGO (47 % vs 21 %, P < 0.05). Pathway analysis showed the epigenetic regulation pathway was more frequently affected in GGO subgroup, while impaired apoptosis/cell cycle pathway was more enriched in non-GGO LUADs.

CONCLUSIONS

Our longitudinal ctDNA monitoring data showed that undetectable ctDNA may predict low risk of tumor recurrence or metastasis in postoperative (p)stage I LUAD patients, while it requires further investigation on how robust the positive ctDNA results could predict tumor relapse in these patients.

CLINICAL REGISTRATION NUMBER

NCT03172156.

Stepwise flowchart for decision making on sublobar resection through the estimation of spread through air space in early stage lung cancer1

OBJECTIVES

The sensitivity for tumor spread through air space (STAS), an independent risk factor for locoregional recurrence after sublobar resection for lung cancer, has been relatively low in frozen sections. We aimed to determine predictors with high negative predictive value for the presence of STAS and to provide the flowchart in combination with these predictors for the decision-making for sublobar resection.

MATERIALS AND METHODS

Between July 2015 and December 2017, 387 patients who underwent surgery for non-small cell lung cancer (NSCLC) with pathologic findings of the total masses measuring ≤ 2 cm were enrolled. The lesions were divided into two groups according to presence of STAS. We compared the preoperative characteristics, operative data, and developed a flowchart for STAS prediction using receiver operator characteristic curve analysis and multivariable logistic regression.

RESULTS

The STAS-positive group (N = 111) had a significantly higher preoperative tumor size (1.70 [1.5] vs 1.50 [0.69], p < 0.001) and standardized uptake value tumor-to-liver (SUV T/L) ratio (1.40 [1.60] vs 0.60 [1.10], p < 0.001) and a significantly lower two-dimensional ground-glass opacity (GGO) percentage (35.86 [61.00] vs 78.14 [39.00], p < 0.001). Meanwhile, the STAS-negative group (N = 286) had higher lepidic predominance (41.6% vs. 1.8%, p < 0.001). We developed a flowchart for predicting STAS in combination with two-dimensional GGO percentage on computed tomography (CT), SUV T/L ratio on positron-emission CT, and lepidic predominant pattern. The sensitivity, specificity, and negative predictive value for STAS positivity were 79.3%, 68.5%, and 89.5%, respectively.

CONCLUSIONS

The stepwise flowchart using two-dimensional GGO percentage on CT, maximum SUV, and lepidic predominance might be helpful in selecting patients with early NSCLC for sublobar resection.

Spread Through Air Spaces (STAS) Is Prognostic in Atypical Carcinoid, Large Cell Neuroendocrine Carcinoma, and Small Cell Carcinoma of the Lung

INTRODUCTION

Tumor spread through air spaces (STAS) has prognostic significance in lung adenocarcinoma and squamous cell carcinoma. We sought to investigate the prognostic importance of STAS in lung neuroendocrine tumors (NETs).

METHODS

All tumor slides from patients with resected pathologic stage I to III lung NETs (N = 487) (299 with typical carcinoid [TC], 38 with atypical carcinoid [AC], 93 with large cell neuroendocrine carcinoma [LCNEC], and 57 with SCLC) treated between 1992 and 2012 were evaluated for presence of STAS. Cumulative incidence of recurrence (CIR) and lung cancer-specific cumulative incidence of death (LC-CID) were analyzed by using a competing-risks approach.

RESULTS

STAS was identified in 26% of NETs (16% of TCs, 37% of ACs, 43% of LCNECs, and 46% of SCLCs). STAS was associated with distant metastasis, as well as with higher CIR and LC-CID in the overall cohort and in the AC, LCNEC, and SCLC cohorts (owing to a small number of recurrences and deaths [<5], prognostic analysis was not performed in the TC cohort). In multivariable analysis stratified by stage, STAS was significantly associated with higher CIR (subhazard ratio = 2.85, 95% confidence interval: 1.73-4.68, p < 0.001) and LC-CID (subhazard ratio = 2.72, 95% confidence interval: 1.57-4.70, p < 0.001), independent of histologic subtype. STAS was independently associated with CIR and LC-CID in the LCNEC cohort and LC-CID in the SCLC cohort.

CONCLUSIONS

In patients with lung NETs, STAS is associated with early distant metastasis and worse LC-CID. In patients with LCNEC or SCLC, STAS is an independent poor prognostic factor.

Tumor Spread Through Air Spaces in Non-Small Cell Lung Cancer: A Systematic Review and Meta-Analysis

BACKGROUND

A series of studies have assessed the clinicopathological features and prognostic impact of spread through air spaces (STAS) in non-small cell lung cancer (NSCLC) bringing conflicting findings so far. We performed a systematic review and meta-analysis to synthesize the available evidence regarding to the prognostic value of STAS in NSCLCs.

METHODS

Studies were identified by searching databases including PubMed, EMBASE, Web of Science, and Cochrane Library up to August 2018 without language restrictions. Results of these searches were filtered according to a set of eligibility criteria and analyzed in line with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines.

RESULTS

A total of 3,754 patients from 14 studies were selected for the present study. The pooled results suggested that presence of STAS was associated with worse recurrence-free survival (hazard ratio [HR], 1.975; 95% confidence interval [CI], 1.691 to 2.307; p < 0.001) and overall survival (HR, 1.75; 95% CI, 1.375 to 2.227; p < 0.001) in NSCLCs. Subgroup analysis by histology type indicated the presence of STAS was significantly associated with inferior recurrence-free survival in resected lung adenocarcinoma (n = 7; HR, 2.288; 95% CI, 1.843 to 2.840; I² = 7.80%), lung squamous cell carcinoma (n = 3; HR, 1.622; 95% CI, 1.279 to 2.056; I² = 0%), and lung pleomorphic carcinoma (n = 1; HR, 4.76; 95% CI, 1.168 to 19.398). Additionally, a number of clinicopathological characteristics indicating STAS in NSCLCs are summarized.

CONCLUSIONS

Our study indicates that tumor STAS was a potentially significant prognostic predictor for surgical patients with NSCLCs. The prognostic impact of STAS present in the resection margin remains undetermined. Further large-scale prospective studies are warranted to confirm the prognostic significance of STAS in patients with NSCLCs.

Predictive value of a prognostic model based on pathologic features in lung invasive adenocarcinoma

OBJECTIVES

Tumor spread through air spaces (STAS) was recently reported as a novel risk factor for the prognosis of patients with resected lung adenocarcinoma that indicates invasive tumor behavior. The purpose of this study was to build a prognostic model consisting of STAS and other pathologic features including visceral pleural invasion (VPI), vascular invasion (VI) and histological subtype (HS) in lung invasive adenocarcinoma.

MATERIALS AND METHODS

A total of 289 patients with resected lung invasive adenocarcinomas ≤4 cm were analyzed retrospectively to evaluate the potential prognostic value of STAS, VPI, VI and HS for recurrence-free survival (RFS) and overall survival (OS).

RESULTS

STAS was observed in 143 patients (49.5%). Univariate and multivariate analysis showed that STAS, VPI, VI and HS were significant prognostic factors for poorer RFS and OS. Thus, a prognostic model including STAS, VPI, VI and HS was built using the results of the multivariate analysis. Nomograms were developed to predict the 5-year RFS and OS. The concordance index (C-index) of the prognostic model was 0.8122 for predicting 5-year RFS and 0.8539 for predicting 5-year OS in the internal validation. Moreover, the calibration curves for the 5-year RFS and OS showed that the nomograms were calibrated well. In addition, a similar predicted capability of the prognostic model was observed in the validation cohort.

CONCLUSION

STAS, VPI, VI and HS were significant prognostic factors for poorer RFS and OS. The prognostic model including STAS, VPI, VI and HS could effectively predict prognosis.