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Meta-analysis of association between CT-based features and tumor spread through air spaces in lung adenocarcinoma.

ABSTRACT: OBJECTIVE:Spread through air space (STAS) is a novel invasive pattern of lung adenocarcinoma and is also a risk factor for recurrence and worse prognosis of lung adenocarcinoma after sublobar resection. The aims of this study are to evaluate the association between computed tomography (CT)-based features and STAS for preoperative prediction of STAS in lung adenocarcinoma, eventually, which could help us choose appropriate surgical type. METHODS:Systematic research was conducted to search for studies published before September 1, 2019. The association between CT-based features of radiological tumor size>2?cm?pure solid nodule? part-solid nodule or Percentage of solid component (PSC)>50% and STAS was evaluated. According to rigorous inclusion and exclusion criteria. Eight studies including 2385 patients published between 2015 and 2018 were finally enrolled in our meta-analysis. RESULTS:Our results clearly depicted that there is no significant relationship between radiological tumor size>2?cm and STAS with the combined OR of 1.47(95% CI:0.86-2.51). Meta-analysis of 3 studies showed that pure solid nodule in CT image were more likely to spread through air spaces with pooled OR of 3.10(95%CI2.17-4.43). Meta-analysis of 5 studies revealed the part-solid nodule in CT image may be more likely to appear STAS in adenocarcinoma (ADC) (combined OR:3.10,95%CI:2.17-4.43). PSC>50% in CT image was a significant independent predictor in the diagnosis of STAS in ADC from our meta-analysis with combined OR of 2.95(95%CI:1.88-4.63). CONCLUSION:In conclusion, The CT-based features of pure solid nodule?part-solid nodule?PSC>50% are promising imaging biomarkers for predicting STAS in ADC and may substantially influence the choice of surgical type. In future, more studies with well-designed and large-scale are needed to confirm the conclusion.

SUBMITTER: Yin Q

PROVIDER: S-EPMC7488257 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Meta-analysis of association between CT-based features and tumor spread through air spaces in lung adenocarcinoma.

Yin Qifan Q Wang Huien H Cui Hongshang H Wang Wenhao W Yang Guang G Qie Peng P Xun Xuejiao X Han Shaohui S Liu Huining H

Journal of cardiothoracic surgery 20200910 1

<h4>Objective</h4>Spread through air space (STAS) is a novel invasive pattern of lung adenocarcinoma and is also a risk factor for recurrence and worse prognosis of lung adenocarcinoma after sublobar resection. The aims of this study are to evaluate the association between computed tomography (CT)-based features and STAS for preoperative prediction of STAS in lung adenocarcinoma, eventually, which could help us choose appropriate surgical type.<h4>Methods</h4>Systematic research was conducted to ...[more]

PMID: 32912289

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Project description:BackgroundThe benefit of adjuvant chemotherapy (ACT) remains unknown for patients with stage I lung adenocarcinoma (ADC) with spread through air spaces (STAS). This study investigated the effect of adjuvant chemotherapy in stage I ADC/STAS-positive patients.MethodsA total of 3346 patients with stage I ADC from five institutions in China were identified from 2009 to 2013, of whom 1082 were diagnosed with STAS (32.3%). By using the Kaplan-Meier method and Cox proportional hazard regression model, we explored the impact of STAS on prognosis, and determined if the use of adjuvant chemotherapy was associated with improved outcomes in patients with stage I ADC/STAS-positive. A validation cohort was also included in this study.ResultsPatients with stage I ADC/STAS-positive in the primary cohort had unfavorable overall survival (OS) and disease-free survival (DFS). A multivariate Cox regression model confirmed the survival disadvantages of STAS in patients with stage I ADC [OS: hazards ratio (HR) = 1.877, 95% confidence interval (CI): 1.579-2.231; p < 0.001; DFS: HR = 1.895, 95% CI: 1.614-2.225; p < 0.001]. Lobectomy was associated with better OS and DFS than sublobar resection (SR) in both stage IA and IB ADC/STAS-positive. Similar results were observed in the validation cohort. For patients with stage IB ADC/STAS-positive, ACT was revealed as an independent factor for favorable survival (OS: HR = 0.604, 95% CI: 0.397-0.919; p = 0.018; DFS: HR = 0.565, 95% CI: 0.372-0.858; p = 0.007). However, among patients with stage IA ADC/STAS-positive, ACT was associated with improved outcomes only for those undergoing SR (OS: HR = 0.787, 95% CI: 0.359-0.949; p = 0.034; DFS: HR = 0.703, 95% CI: 0.330-0.904; p = 0.029).ConclusionThe presence of STAS was correlated with poor prognosis in patients with stage I ADC. Our study suggested that ACT might be considered for patients with stage IB ADC/STAS-positive and those with stage IA ADC/STAS-positive who underwent SR.

Project description:Background Spread through air space (STAS) is a novel invasive pattern of lung adenocarcinoma and is also a risk factor for recurrence and worse prognosis of lung adenocarcinoma. This study aimed to develop and validate a computed tomography (CT)-based logistic regression model to predict STAS in lung adenocarcinoma. Methods This retrospective study was approved by the institutional review board of two centers and included 578 patients (462 from center I and 116 from center II) with pathologically confirmed lung adenocarcinoma. STAS was identified from 90 center I patients (19.5%) and 28 center II patients (24.1%) from. The maximum diameter, nodule area, and area of solid components in part-solid nodules were measured. Twenty-one semantic characteristics were assessed. Univariate analysis was used to select CT characteristics, which were associated with STAS in the patient cohort of center I. Multivariable logistic regression was used to develop a CT characteristics-based model on those variables with statistical significance. The model was validated in the validation cohort and then tested in the external test cohort (patients from center II). The diagnostic performance of the model was measured by area under the curve (AUC) of receiver operating characteristic (ROC). Results At univariate analysis, age and 11 CT characteristics, including the maximum diameter of the tumor, the maximum area of the tumor, the area and ratio of the solid component, nodule type, pleural thickening, pleural retraction, mediastinal lymph node enlargement, vascular cluster sign, and lobulation, specula were found to be significantly associated with STAS. The optimal logistic regression model included age, maximum diameter and ratio of solid component with odds ratio (OR) value of 0.967 (95% CI: 0.944–0.988), 1.027 (95% CI: 1.008–1.046) and 5.14 (95% CI: 2.180–13.321), respectively. This model achieved an AUC of 0.801 (95% CI: 0.709–0.892) and 0.692 (95% CI: 0.518–0.866) in the validation cohort and the external test cohort, respectively. The difference was not statistically significant (P=0.280). Conclusions CT-based logistic regression machine learning model could preoperatively predict STAS in lung adenocarcinoma with excellent diagnosis performance, which could be supplementary to routine CT interpretation.

Project description:Background Spread through air spaces (STAS), as a new pattern of invasion, was officially proposed by the World Health Organization (WHO) in 2015, and its importance was reiterated in 2021. Since it was proposed, numerous studies have confirmed that STAS is associated with poor prognosis, but there are relatively few studies related to the prognosis of postoperative patients with lung squamous cell carcinoma. By synthesizing different predictive variables, nomogram can obtain the individual digital probability of clinical events succinctly and intuitively, which can meet our needs for personalized medicine. In this study, our goal is to explore the prognostic value of STAS in lung squamous cell carcinoma and establish a prognostic prediction model. Methods Under six inclusion criteria, 540 postoperative patients were enrolled in the study. STAS was re-evaluated by pathologists at Ningbo Clinicopathological Diagnosis Center. Progression-free survival (PFS) referred to the time from randomization to the first occurrence of disease progression or death of any cause. Recurrences were confirmed by clinical, radiological or pathological assessment. The survival information was collected by telephone and outpatient follow-up. A total of 540 patients were randomly divided into groups in a 6:4 ratio for survival analysis to determine the correlation between STAS and prognosis. Cox regression was used for univariate and multivariate analysis, so as to establish a predictive model. The assessment of the nomogram was carried out by receiver operating characteristic (ROC) curve analysis, calibration curve analysis and decision curve analysis (DCA). Results The overall 5-year survival rate was 70.35% in STAS-negative patients and 42.35% in STAS-positive patients. In all cohorts, STAS-negative patients had longer 5-year PFS than STAS-positive patients (P<0.001). Multivariate analysis showed that stage [stage II P=0.008, hazard ratio (HR) =1.792; stage III P<0.001, HR =3.148], tumor differentiation (well-differentiation P=0.021, HR =0.436), and STAS (P=0.026, HR =1.470) were independent predictors of PFS. The area under the curve (AUC) of model 5 in discovery cohort is 0.720, while the AUC of model 5 in validation cohort is 0.693. Conclusions The nomogram combined with STAS can provide a personalized visual survival probability prediction map for postoperative patients with lung squamous cell carcinoma, so as to aid in the pursuit of personalized medicine to a certain extent.

Dataset Information

Meta-analysis of association between CT-based features and tumor spread through air spaces in lung adenocarcinoma.

Publications

Meta-analysis of association between CT-based features and tumor spread through air spaces in lung adenocarcinoma.

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