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INTRODUCTION: To facilitate global implementation of lung cancer (LC) screening and early detection in a quality assured and consistent manner, common terminology is needed. Researchers and clinicians within different specialties may use the same terms but with different meanings or different terms for the same intended meanings. METHODS: The Diagnostics Working Group of the International Association for the Study of Lung Cancer Early Detection and Screening Committee has analyzed and discussed relevant terms used on a regular basis and suggests recommendations for consensus definitions of terminology applicable in this setting. We explored how to reach consensus to define relevant and unambiguous terminology for use by health care providers, researchers, patients, screening participants, and family. RESULTS: Terms and definitions for epidemiologic and health-economical purposes included the following: standardized incidence and mortality rates, LC-specific survival, long-term survival and cure rates, overdiagnosis, overtreatment, and undertreatment. Terms and definitions for defining screening findings included the following: positive, false-positive, negative, false-negative, and indeterminate findings and additional and incidental findings. Terms and definitions for describing parameters in screening programs included the following: opportunistic versus programmatic screening, screening rounds, interval or interim diagnoses, and invasive and minimally invasive procedures. Terms and definitions for shared decision-making included the following: LC screening-possible harms and risks and LC risk and modifiers prior and posterior to a measure. CONCLUSIONS: A common set of terminology with standard definitions is recommended for describing clinical LC screening programs, the discussion about effectiveness and outcomes, or the clinical setting. The use of the terms should be clearly defined and explained.
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PURPOSE: We aimed to evaluate the efficiency of computed tomography (CT) radiomic features extracted from gross tumor volume (GTV) and peritumoral volumes (PTV) of 5, 10, and 15 mm to identify the tumor grades corresponding to the new histological grading system proposed in 2020 by the Pathology Committee of the International Association for the Study of Lung Cancer (IASLC). METHODS: A total of 151 lung adenocarcinomas manifesting as pure ground-glass lung nodules (pGGNs) were included in this randomized multicenter retrospective study. Four radiomic models were constructed from GTV and GTV + 5/10/15-mm PTV, respectively, and compared. The diagnostic performance of the different models was evaluated using receiver operating characteristic curve analysis RESULTS: The pGGNs were classified into grade 1 (117), 2 (34), and 3 (0), according to the IASLC grading system. In all four radiomic models, pGGNs of grade 2 had significantly higher radiomic scores than those of grade 1 (P < 0.05). The AUC of the GTV and GTV + 5/10/15-mm PTV were 0.869, 0.910, 0.951, and 0.872 in the training cohort and 0.700, 0.715, 0.745, and 0.724 in the validation cohort, respectively. CONCLUSIONS: The radiomic features we extracted from the GTV and PTV of pGGNs could effectively be used to differentiate grade-1 and grade-2 tumors. In particular, the radiomic features from the PTV increased the efficiency of the diagnostic model, with GTV + 10 mm PTV exhibiting the highest efficacy.
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Neoplasias Pulmonares , Tomografía Computarizada por Rayos X , Humanos , Estudios Retrospectivos , Masculino , Femenino , Neoplasias Pulmonares/diagnóstico por imagen , Neoplasias Pulmonares/patología , Neoplasias Pulmonares/clasificación , Tomografía Computarizada por Rayos X/métodos , Persona de Mediana Edad , Anciano , Adenocarcinoma del Pulmón/diagnóstico por imagen , Adenocarcinoma del Pulmón/patología , Adenocarcinoma del Pulmón/clasificación , Carga Tumoral , Clasificación del Tumor , Nódulos Pulmonares Múltiples/diagnóstico por imagen , Nódulos Pulmonares Múltiples/patología , Nódulos Pulmonares Múltiples/clasificación , RadiómicaRESUMEN
INTRODUCTION: The International Association for the Study of Lung Cancer (IASLC) grading system predicts early lung adenocarcinoma outcomes. METHODS: The purpose of this study is to examine prognostic value of the IASLC grading system and its association with the tumor microenvironment (TME) in Stage I EGFR-muted lung adenocarcinoma. Based on the IASLC grading system, we compared the clinicopathological characteristics of EGFR-mutated lung adenocarcinoma (n = 296). In addition, we examined the expression level of E-cadherin in tumor cells and counted the number of tumor-infiltrating lymphocytes (TILs; CD8, CD20, CD138, and Foxp3), tumor-associated macrophages (TAMs; CD204), and cancer-associated fibroblasts (CAFs; podoplanin) using semi-automatic digital pathology image analysis. RESULTS: Recurrence-free survival (RFS) curve showed that survival of grade 3 was significantly shorter than that of grade 1 (P < 0.01) and grade 2 (P = 0.03). Multivariate analysis of RFS revealed the invasive size, lymphatic permeation, and grade 3 (P < 0.01) as independent poor prognostic factors. The number of CD204 +TAMs and PDPN+CAFs was significantly higher in grade 3 than in grade 1 or 2 (all P < 0.01). Among the intermediate grade by the predominant subtype based classification, cases classified as grade 3 by the new classification had higher number of CD204 +TAMs (P < 0.01) and PDPN+CAFs (P = 0.02) than those classified as grade 2. CONCLUSION: The IASLC grading system correlated with the outcomes of EGFR-mutated lung adenocarcinoma. Grade 3 was found to have the TME that most contributes to tumor progression, which probably explained their poor prognosis.
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Adenocarcinoma del Pulmón , Receptores ErbB , Neoplasias Pulmonares , Mutación , Microambiente Tumoral , Humanos , Masculino , Receptores ErbB/genética , Receptores ErbB/metabolismo , Femenino , Adenocarcinoma del Pulmón/patología , Adenocarcinoma del Pulmón/genética , Adenocarcinoma del Pulmón/mortalidad , Neoplasias Pulmonares/patología , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/mortalidad , Pronóstico , Persona de Mediana Edad , Anciano , Estadificación de Neoplasias , Clasificación del Tumor , Linfocitos Infiltrantes de Tumor/patología , Fibroblastos Asociados al Cáncer/patología , Fibroblastos Asociados al Cáncer/metabolismo , Adulto , Macrófagos Asociados a Tumores , Anciano de 80 o más Años , Estudios RetrospectivosRESUMEN
Introduction: EGFR exon 20 insertion (ex20ins) mutations account for approximately 10% of EGFR mutations in lung adenocarcinoma. Patients with ex20ins mutation do not respond to standard EGFR tyrosine kinase inhibitor therapy. In this work, we analyzed the characteristics, treatment patterns, and outcomes in this subgroup of patients with NSCLC. Methods: The American Society of Clinical Oncology CancerLinQ Discovery data set was queried to identify patients with initial diagnosis of NSCLC between the years 1995 and 2018 and with EGFR ex20ins mutations. Data were extracted on patient demographics, tumor characteristics, treatments, and outcomes, and compared using chi-square and analysis of variance. Kaplan-Meier curves were generated to compare overall survival with log-rank tests. All analyses were performed using Python 3.6 (Python Software Foundation). Results: A total of 357 patients were eligible. Patient characteristics include a median age of 68 years comprising female sex of 54%, White race of 63%, and Black race of 9%. Approximately 62% of total patients had stage 4 disease, and 30% of all patients had brain metastasis. There were 54% of patients who were treated with chemotherapy and 15% with immune checkpoint inhibitors (ICIs). In patients with brain metastasis, 16% were treated with ICI, 18% with targeted therapy, and 59% with chemotherapy. The median survival of the entire group was 23.8 months. Among patients with stage 4 disease (n = 222): 51% were women, 64% were white, 37% had brain metastasis, 18% were treated with ICI, 14% had targeted therapy, and 60% were treated with chemotherapy. Stage 4 patients treated with targeted therapy had better survival compared with those who did not receive targeted therapy (20.6 versus 16.1 mo, p = 0.02). Univariate and multivariate analyses suggested favorable outcomes for patients treated with immunotherapy. Conclusions: EGFR ex20ins mutation represents a unique subset of NSCLC; it is associated with a higher propensity for brain metastases and a relatively modest overall survival. Novel treatment approaches are urgently needed to improve patient outcomes.
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OBJECTIVE: There is a lack of knowledge regarding the use of prognostic features in stage I lung adenocarcinoma (LUAD). Thus, we investigated clinicopathologic features associated with recurrence after complete resection for stage I LUAD. METHODS: We performed a retrospective analysis of patients with pathologic stage I LUAD who underwent R0 resection from 2010 to 2020. Exclusion criteria included history of lung cancer, induction or adjuvant therapy, noninvasive or mucinous LUAD, and death within 90 days of surgery. Fine and Gray competing-risk regression assessed associations between clinicopathologic features and disease recurrence. RESULTS: In total, 1912 patients met inclusion criteria. Most patients (1565 [82%]) had stage IA LUAD, and 250 developed recurrence: 141 (56%) distant and 109 (44%) locoregional only. The 5-year cumulative incidence of recurrence was 12% (95% CI, 11%-14%). Higher maximum standardized uptake value of the primary tumor (hazard ratio [HR], 1.04), sublobar resection (HR, 2.04), higher International Association for the Study of Lung Cancer grade (HR, 5.32 [grade 2]; HR, 7.93 [grade 3]), lymphovascular invasion (HR, 1.70), visceral pleural invasion (HR, 1.54), and tumor size (HR, 1.30) were independently associated with a hazard of recurrence. Tumors with 3 to 4 high-risk features had a higher cumulative incidence of recurrence at 5 years than tumors without these features (30% vs 4%; P < .001). CONCLUSIONS: Recurrence after resection for stage I LUAD remains an issue for select patients. Commonly reported clinicopathologic features can be used to define patients at high risk of recurrence and should be considered when assessing the prognosis of patients with stage I disease.
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BACKGROUND: The International Association for the Study of Lung Cancer (IASLC) Pathology Committee introduced a histologic grading system for invasive lung adenocarcinoma (LUAD) in 2020. The IASLC grading system, hinging on the evaluation of predominant and high-grade histologic patterns, has proven to be practical and prognostic for invasive LUAD. However, there are still limitations in evaluating the prognosis of stage IA LUAD. Radiomics may serve as a valuable complement. PURPOSE: To establish a model that integrates IASLC grading and radiomics, aimed at predicting the prognosis of stage IA LUAD. METHODS: We conducted a retrospective analysis of 628 patients diagnosed with stage IA LUAD who underwent surgical resection between January 2015 and December 2018 at our institution. The patients were randomly divided into the training set (n = 439) and testing set (n = 189) at a ratio of 7:3. Overall survival (OS) and disease-free survival (DFS) were taken as the end points. Radiomics features were obtained by PyRadiomics. Feature selection was performed using the least absolute shrinkage and selection operator (LASSO). The prediction models for OS and DFS were developed using multivariate Cox regression analysis, and the models were visualized through nomogram plots. The model's performance was evaluated using area under the curves (AUC), concordance index (C-index), calibration curves, and survival decision curve analysis (DCA). RESULTS: In total, nine radiomics features were selected for the OS prediction model, and 15 radiomics features were selected for the DFS prediction model. Patients with high radiomics scores were associated with a worse prognosis (p < 0.001). We built separate prediction models using radiomics or IASLC alone, as well as a combined prediction model. In the prediction of OS, we observed that the combined model (C-index: 0.812 ± 0.024, 3 years AUC: 0.692, 5 years AUC: 0.792) achieved superior predictive performance than the radiomics (C-index: 0.743 ± 0.038, 3 years AUC: 0.633, 5 years AUC: 0.768) and IASLC grading (C-index: 0.765 ± 0.042, 3 years AUC: 0.658, 5 years AUC: 0.743) models alone. Similar results were obtained in the models for DFS. CONCLUSION: The combination of radiomics and IASLC pathological grading proves to be an effective approach for predicting the prognosis of stage IA LUAD. This has substantial clinical relevance in guiding treatment decisions for early-stage LUAD.
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AIMS: Tumour grading is an essential part of the pathologic assessment that promotes patient management. The International Association for the Study of Lung Cancer (IASLC) proposed a grading system for non-mucinous lung adenocarcinoma in 2020. We aimed to validate the prognostic impact of this novel grading system on overall survival (OS) and recurrence-free survival (RFS) based on literature data. METHODS AND RESULTS: The review protocol was registered in PROSPERO (CRD42023396059). We aimed to identify randomized or non-randomized controlled trials published after 2020 comparing different IASLC grade categories in Medline, Embase, and CENTRAL. Hazard ratios (HRs) with 95% confidence intervals (CIs) of OS and RFS were pooled and the Quality In Prognosis Studies (QUIPS) tool was used to assess the risk of bias in the included studies. Ten articles were eligible for this review. Regarding OS estimates, grade 1 lung adenocarcinomas were better than grade 3 both in univariate and multivariate analyses (HROSuni = 0.19, 95% CI: 0.05-0.66, p = 0.009; HROSmulti = 0.21, 95% CI: 0.12-0.38, p < 0.001). Regarding RFS estimates, grade 3 adenocarcinomas had a worse prognosis than grade 1 in multivariate analysis (HRRFSmulti: 0.22, 95% CI: 0.14-0.35, p < 0.001). CONCLUSION: The literature data and the result of our meta-analysis demonstrate the prognostic relevance of the IASLC grading system. This supports the inclusion of this prognostic parameter in daily routine worldwide.
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Adenocarcinoma del Pulmón , Neoplasias Pulmonares , Clasificación del Tumor , Humanos , Neoplasias Pulmonares/patología , Neoplasias Pulmonares/mortalidad , Neoplasias Pulmonares/diagnóstico , Adenocarcinoma del Pulmón/patología , Adenocarcinoma del Pulmón/mortalidad , Adenocarcinoma del Pulmón/diagnóstico , Pronóstico , Clasificación del Tumor/métodosRESUMEN
BACKGROUND: Despite promising overall survival of stage I lung adenocarcinoma (LUAD) patients, 10-25 % of them still went through recurrence after surgery. [1] While it is still disputable whether adjuvant chemotherapy is necessary for stage I patients. [2] IASLC grading system for non-mucinous LUAD shows that minor high-grade patterns are significant indicator of poor prognosis. [3] Other risk factors, such as, pleura invasion, lympho-vascular invasion, STAS, etc. are also related to poor prognosis. [4-6] There still lack evidence whether IASLC grade itself or together with other risk factors can guide the use of adjuvant therapy in stage I patients. In this article, we tried to establish a multi-variable recurrence prediction model for stage I LUAD patients that is able to identify candidates of adjuvant chemotherapy. METHODS: We retrospectively collected patients who underwent lung surgery from 2018.8.1 to 2018.12.31 at our institution and diagnosed with lung adenocarcinoma pT1-2aN0M0 (stage I). Clinical data, manifestation on CT scan, pathologic features, driver gene mutations and follow-up information were collected. Cox proportional hazards regression analyses were performed utilizing the non-adjuvant cohort to predict disease free survival (DFS) and a nomogram was constructed and applied to the total cohort. Kaplan-Meier method was used to compare DFS between groups. Statistical analysis was conducted by R version 3.6.3. FINDINGS: A total of 913 stage I LUAD patients were included in this study. Median follow-up time is 48.1 months.4-year and 5-year DFS are 92.9 % and 89.6 % for the total cohort. 65 patient experienced recurrence or death. 4-year DFS are 97.0 %,94.6 % and 76.2 %, and 5-year DFS are 95.5 %, 90.0 % and 74.1 % in IASLC Grade1, 2 and 3, respectively(p < 0.0001). High-risk patients defined by single risk factors, such as, IASLC grade 3, pleura invasion, STAS, less LN resected could not benefit from adjuvant therapy. A LASSO-COX regression model was built and patients are divided into high-risk and low-risk groups. In the high-risk group, patients underwent adjuvant chemotherapy have longer DFS than those who did not (p = 0.024), while in the low-risk group, patients underwent adjuvant chemotherapy have inferior DFS than those who did not (p < 0.001). INTERPRETATION: IASLC grading is a significant indicator of DFS, however it could not guide adjuvant therapy in our stage I LUAD cohort. Growth patterns and T indicators together with other risk factors could identify high-risk patients that are potential candidate of adjuvant therapy, including some stage IA LUAD patients.
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Adenocarcinoma del Pulmón , Adenocarcinoma , Neoplasias Pulmonares , Humanos , Neoplasias Pulmonares/patología , Estudios Retrospectivos , Adenocarcinoma/tratamiento farmacológico , Adenocarcinoma/patología , Adenocarcinoma del Pulmón/tratamiento farmacológico , Adenocarcinoma del Pulmón/patología , Quimioterapia Adyuvante , Estadificación de Neoplasias , PronósticoRESUMEN
Introduction: To validate the residual tumor (R) classification proposed by the International Association for the Study of Lung Cancer (IASLC) in NSCLC after sleeve lobectomy. Methods: A total of 682 patients were analyzed. The R status, on the basis of the Union for International Cancer Control (UICC) criteria, was recategorized according to the IASLC descriptors. Recurrence-free survival (RFS) and overall survival (OS) among different R classifications were assessed for the entire cohort and pathologic node (pN) subgroups. Results: All in all, 631 (92.5%), 48 (7.1%), and three patients (0.4%) were classified as R0, R1, and R2, respectively, by the UICC criteria, whereas 489 (71.7%), 110 (16.1%), and 83 patients (12.2%), received R0, uncertain resection (R[un]), and R1/2 resection, respectively, according to the IASLC criteria. There were 96 patients (15.2%) with UICC R0 who were reclassified as R(un), mainly because of the positive highest mediastinal node station (82 of 96, 85.4%). A total of 46 patients (7.3%) were reassigned from UICC R0 to IASLC R1/2 owing to extracapsular extension. For the entire cohort, patients with R(un) and R1/2 exhibited worse RFS (R[un], adjusted p = 0.023; R1/2, adjusted p = 0.001) and OS (R[un], adjusted p = 0.040; R1/2, adjusted p = 0.051) compared with R0. No significant differences were observed between R(un) and R1/2 (RFS, adjusted p = 0.586; OS, adjusted p = 0.781). Furthermore, subgroup analysis revealed a distinct prognostic impact of the IASLC R status-with prognostic significances in the pN1 and pN2 subgroups, but not in the pN0 subgroup. Conclusions: The IASLC R descriptors helped to stratify the prognosis of NSCLC after sleeve lobectomy, with its prognostic impact varied among pN stages.
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PURPOSE: The new grading system for invasive nonmucinous lung adenocarcinoma (LUAD) in the 2021 World Health Organization Classification of Thoracic Tumors was based on a combination of histologically predominant subtypes and high-grade components. In this study, a model for the pretreatment prediction of grade 3 tumors was established according to new grading standards. METHODS: We retrospectively collected 399 cases of clinical stage I (cStage-I) LUAD surgically treated in Tianjin Chest Hospital from 2015 to 2018 as the training cohort. Besides, the validation cohort consists of 216 patients who were collected from 2019 to 2020. These patients were also diagnosed with clinical cStage-I LUAD and underwent surgical treatment at Tianjin Chest Hospital. Univariable and multivariable logistic regression analyses were used to select independent risk factors for grade 3 adenocarcinomas in the training cohort. The nomogram prediction model of grade 3 tumors was established by R software. RESULTS: In the training cohort, there were 155 grade 3 tumors (38.85%), the recurrence-free survival of which in the lobectomy subgroup was better than that in the sublobectomy subgroup (P = 0.034). After univariable and multivariable analysis, four predictors including consolidation-to-tumor ratio, CEA level, lobulation, and smoking history were incorporated into the model. A nomogram was established and internally validated by bootstrapping. The Hosmer-Lemeshow test result was χ2 = 7.052 (P = 0.531). The C-index and area under the receiver operating characteristic curve were 0.708 (95% CI: 0.6563-0.7586) for the training cohort and 0.713 (95% CI: 0.6426-0.7839) for the external validation cohort. CONCLUSIONS: The nomogram prediction model of grade 3 LUAD was well fitted and can be used to assist in surgical or adjuvant treatment decision-making.
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Adenocarcinoma del Pulmón , Adenocarcinoma , Neoplasias Pulmonares , Humanos , Estudios Retrospectivos , Pronóstico , Adenocarcinoma del Pulmón/cirugía , Adenocarcinoma/patologíaRESUMEN
BACKGROUND: The prognostic impact of EGFR mutation as major targetable somatic gene variant on lung adenocarcinoma is controversial. KRAS is another major somatic variant in lung adenocarcinoma, and a therapeutic agent for KRAS G12C became available in clinical settings. These mutations represent clinicopathological features of lung adenocarcinoma and can guide the treatment choice after recurrence. We evaluated the prognostic impact of EGFR and KRAS mutations by considering other clinicopathological recurrence risks in resected pTis-3N0M0 lung adenocarcinoma. METHODS: Clinicopathological features related to recurrence and genetic status were estimated in consecutive 877 resected cases. Recurrence-free survival (RFS), cumulative recurrence rate (CRR), and overall survival (OS) were compared. Uni- and multivariate analyses for RFS were performed after excluding cases with little or no recurrence risks. RESULTS: EGFR mutation was more likely to be harbored in female, never-smoker, or patients accompanied by > 5% lepidic component. KRAS mutation was more likely to be harbored in patients with current/ex-smoking history, International Association for the Study of Lung Cancer (IASLC) grade 3, or accompanied lymphatic or vascular invasion. In IASLC grade 2 and 3 patients, EGFR or KRAS mutation cases had significantly worse 5-year RFS than wild type patients (76.9% vs. 85.0%, hazard ratio [HR] = 1.55, 95% confidence interval [CI] = 1.62-6.41, P < 0.001). EGFR or KRAS mutation cases had significantly higher 5-year CRR than wild type patients (17.7% vs. 9.8%, HR = 1.69, 95% CI = 1.44-6.59, P = 0.0038). KRAS mutation cases had higher 5-year CRR than EGFR mutation cases (16.7% vs. 21.4%, HR = 1.62, 95% CI = 0.96-7.19, P = 0.061). There was no significant difference in OS between cohorts. Multivariate analysis revealed that a positive EGFR/KRAS mutation status was risk factor for worse RFS (HR = 2.007, 95% CI = 1.265-3.183, P = 0.003). CONCLUSION: Positive EGFR and KRAS mutation statuses were risk factors for recurrence in resected IASLC grade 2 and 3 patients. KRAS mutations were more likely to be confirmed in cases with an increased risk of recurrence. EGFR and KRAS mutation statuses should be evaluated simultaneously when assessing the risk of recurrence.
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Adenocarcinoma del Pulmón , Neoplasias Pulmonares , Humanos , Femenino , Pronóstico , Proteínas Proto-Oncogénicas p21(ras)/genética , Estadificación de Neoplasias , Adenocarcinoma del Pulmón/genética , Adenocarcinoma del Pulmón/patología , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/cirugía , Procesos Neoplásicos , Mutación , Receptores ErbB/genéticaRESUMEN
Objectives: This study aimed to identify the computed tomography (CT) features associated with the new International Association for the Study of Lung Cancer (IASLC) three-tiered grading system to improve the preoperative prediction of disease-free survival of stage I lung adenocarcinoma patients. Methods: The study included 379 patients. Ordinal logistic regression analysis was used to identify the independent predictors of IASLC grades. The first multivariate Cox regression model (Model 1) was based on the significant factors from the univariate analysis. The second multivariate model (Model 2) excluded the histologic grade and based only on preoperative factors. Results: Larger consolidation tumor ratio (OR=2.15, P<.001), whole tumor size (OR=1.74, P=.002), and higher CT value (OR=3.77, P=.001) were independent predictors of higher IASLC grade. Sixty patients experienced recurrences after 70.4 months of follow-up. Model 1 consisted of age (HR:1.05, P=.003), clinical T stage (HR:2.32, P<.001), histologic grade (HR:4.31, P<.001), and burrs sign (HR:5.96, P<.001). Model 2 consisted of age (HR,1.04; P=.015), clinical T stage (HR:2.49, P<.001), consolidation tumor ratio (HR:2.49, P=.016), whole tumor size (HR:2.81, P=.022), and the burrs sign (HR:4.55, P=.002). Model 1 had the best prognostic predictive performance, followed by Model 2, clinical T stage, and histologic grade. Conclusion: CTR (cut-off values of <25% and ≥75%) and whole tumor size (cut-off value of 17 mm) could stratify patients into different prognosis and be used as preoperative surrogates for the IASLC grading system. Integrating these CT features with clinical T staging can improve the preoperative prognostic prediction for stage I lung adenocarcinoma patients.
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To validate the efficiency of pathologic grading system in pathologic stage IA lung adenocarcinoma (LUAD), and explore whether integrating preoperative radiological features would enhance the performance of recurrence discrimination. We retrospectively collected 510 patients with resected stage IA LUAD between January 2012 and December 2019 from Guangdong Provincial People's Hospital (GDPH). Pathologic grade classification of each case was based on the International Association for the Study of Lung Cancer (IASLC) pathologic staging system. Kaplan-Meier curves was used to assess the power of recurrence stratification. Concordance index (C-Index) and receiver operating characteristic curves (ROC) were used for evaluating the clinical utility of different grading systems for recurrence discrimination. Patients of lower IASLC grade showed improved recurrence-free survival (RFS) (P < 0.0001) where numerically difference was found between grade II and grade III (P = 0.119). By integrating the IASLC grading system and radiological feature, we found the RFS rate decreased as the novel radiopathological (RP) grading system increased (P < 0.0001). The difference of RFS curves between any 2 groups as per the RP grading system was statisticallysignificant (RP grade I vs RP grade II, p = 0.007; RP grade I vs RP grade III, P < 0.0001; RP grade II vs RP grade III, P = 0.0003). Compared with the IASLC grading system, the RP grading system remarkably improved recurrence survival discrimination (C-index: 0.822; area under the curve, 0.845). Integrating imaging features into pathologic grading system enhanced the efficiency of recurrence discrimination for resected stage IA LUAD and might help conduct subsequent management.
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INTRODUCTION: The Pathology Committee of the International Association for the Study of Lung Cancer (IASLC) proposed a new histological grading system based on the combination of predominant and high-grade patterns in 2020. MATERIALS AND METHODS: Pathological sections from 631 patients with stage I-III invasive lung adenocarcinoma were reviewed. We then determined the histological grade according to the new grading system and confirmed the pathological features that included the filigree micropapillary and discohesive growth pattern. Applying of the novel IASLC grading system in prognosis stratification was verified and the clinical significance of the pathological characteristics was explored. RESULTS: Cox multivariable analysis revealed that in the stage I-III invasive lung adenocarcinoma, the IASLC grading system was significantly associated with disease-free survival (DFS) [hazard ratio (HR) = 1.419; 95 % confidence interval (CI): 1.040-1.937; P = 0.027] and overall survival (OS) (HR = 1.899; 95 % CI: 1.168-3.087; P = 0.010). In patients with IASLC Grades 1 and 2, the simultaneous presence of filigree micropapillary and discohesive growth pattern was significantly correlated with DFS (HR = 1.899; 95 % CI:1.168-3.087; P = 0.010). However, the filigree micropapillary and discohesive growth pattern did not affect the OS (HR = 2.786; P = 0.317). The competitive risk model revealed that in the stage I cohort, the simultaneous presence of filigree micropapillary and discohesive growth pattern was a risk factor for recurrence and metastasis [sub- distribution HR (SHR) = 1.987; 95 %CI: 1.122-3.518; P = 0.019]. CONCLUSION: Our study verified that the new prognostic stratification system was an effective stratification tool. Filigree micropapillary and discohesive growth pattern may also be risk factors for DFS, postoperative recurrence and metastasis.
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Adenocarcinoma del Pulmón , Adenocarcinoma , Neoplasias Pulmonares , Humanos , Neoplasias Pulmonares/patología , Pronóstico , Adenocarcinoma/patología , Estadificación de Neoplasias , Estudios Retrospectivos , Adenocarcinoma del Pulmón/patologíaRESUMEN
Background: With the popularization of lung cancer screening, more early-stage lung cancers are being detected. This study aims to compare three types of N classifications, including location-based N classification (pathologic nodal classification [pN]), the number of lymph node stations (nS)-based N classification (nS classification), and the combined approach proposed by the International Association for the Study of Lung Cancer (IASLC) which incorporates both pN and nS classification to determine if the nS classification is more appropriate for early-stage lung cancer. Methods: We retrospectively reviewed the clinical data of lung cancer patients treated at the Cancer Hospital, Chinese Academy of Medical Sciences between 2005 and 2018. Inclusion criteria was clinical stage IA lung adenocarcinoma patients who underwent resection during this period. Sub-analyses were performed for the three types of N classifications. The optimal cutoff values for nS classification were determined with X-tile software. KaplanâMeier and multivariate Cox analyses were performed to assess the prognostic significance of the different N classifications. The prediction performance among the three types of N classifications was compared using the concordance index (C-index) and decision curve analysis (DCA). Results: Of the 669 patients evaluated, 534 had pathological stage N0 disease (79.8%), 82 had N1 disease (12.3%) and 53 had N2 disease (7.9%). Multivariate Cox analysis indicated that all three types of N classifications were independent prognostic factors for prognosis (all P < 0.001). However, the prognosis overlaps between pN (N1 and N2, P = 0.052) and IASLC-proposed N classification (N1b and N2a1 [P = 0.407], N2a1 and N2a2 [P = 0.364], and N2a2 and N2b [P = 0.779]), except for nS classification subgroups (nS0 and nS1 [P < 0.001] and nS1 and nS >1 [P = 0.006]). There was no significant difference in the C-index values between the three N classifications (P = 0.370). The DCA results demonstrated that the nS classification provided greater clinical utility. Conclusion: The nS classification might be a better choice for nodal classification in clinical stage IA lung adenocarcinoma.
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Background: The International Association for the Study of Lung Cancer (IASLC) proposed a novel grading system for invasive lung adenocarcinoma, but lymphatic invasion was not evaluated. Meanwhile, the scope of lymph node dissection in part-solid invasive lung adenocarcinoma (PSILA) is still controversial. Therefore, this study aims to explore preoperative risk factors for lymph node metastasis in PSILA, to provide reference for intraoperative dissection of lymph nodes. Methods: From 2018 to 2020, clinical data of patients (stage cN0) consecutively diagnosed as PSILA were retrospectively analyzed and classified according to the novel grading system. Logistic regression was conducted to screen the clinicopathological factors of lymph node metastasis in PSILA. Results: A large cohort of 960 patients with PSILA who underwent lobectomy or sub-lobectomy were enrolled. By logistic regression analyses, solid part size, bronchial cutoff sign, spiculation, and carbohydrate antigen 199 (CA199) were eventually identified as independent risk factors for lymph node metastasis, based on which a nomogram was built to preoperatively predict the risk of lymph node metastasis [area under the receiver operating characteristic curve (AUC)=0.858; concordance index = 0.857; best cutoff, 0.027]. This suggests that intraoperative systematic lymph node dissection is recommended when the predicted risk value exceeds 0.027. Reproducibility of the novel grading system was verified. Conclusions: The novel IASLC grading system was applicative in real world. The nomogram for preoperative prediction of lymph node metastasis may provide reference for the lymph node dissection strategy during PSILA surgeries.
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Background: Complex glandular pattern (CGP) was included as high-grade pattern in the new grading system proposed by The International Association for the Study of Lung Cancer. We aimed to investigate the mutational profile and validate the prognostic significance and proper cut-off value to distinguish the aggressive behavior of CGP. Methods: CGP was defined as nests of tumor cells with sieve-like perforation, fused glands with irregular borders or back-to-back glands without intervening stroma. Patients were categorized into four groups according to the percentage of CGP component (0%, 1-19%, 20-49%, 50-100%). Cox's proportional hazards model was applied to analyze recurrence free survival (RFS) and overall survival (OS). Results: A total of 950 patients with resected lung adenocarcinoma was enrolled. The most frequent driver mutation in this cohort was EGFR and was detected in 624 (65.7%) patients. EGFR mutation was more frequently observed in patients with <20% CGP than in patients with ≥20% CGP (73.6% vs. 60.2%), while KRAS mutation and ALK rearrangement was significantly associated with ≥20% CGP. Patients with 20% or greater CGP exhibited significant worse RFS (P<0.001) and OS (P<0.001) than their counterparts. Moreover, the multivariate Cox regression analysis confirmed that CGP (≥20%) was a risk factor for a worse RFS (P=0.001) and OS (P<0.001) independent of staging and gene mutation. Smaller portion of CGP (<20%) were comparable in RFS and OS to those without CGP (0%). There was also no significant difference in RFS and OS between the 20-49% and ≥50% group. Conclusions: Our study provided mutational profile of patients with different CGP, validated CGP as a negative prognostic factor and provided extra evidences for the optimal cut-off value of CGP percentage.
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INTRODUCTION: The new grading system proposed by the Pathology Committee of the International Association for the Study of Lung Cancer in 2020 was based on the combination of the histologically predominant subtype and high-grade component. Because the predominant subtypes are associated with characteristic subsets, unique subsets can be identified by this grading system. METHODS: We analyzed the clinicopathologic, genotypic, and prognostic features of a cohort of 781 consecutive patients with invasive nonmucinous adenocarcinoma of the lung. RESULTS: Grade 3 tumors were associated with younger age, male sex, a higher smoking dose, and aggressive features (tumor size, lymph node metastasis, stage, lymphovascular invasion, and pleural invasion). Recurrence-free survival and 3-year overall survival were well-stratified according to tumor grade, and the differences were confirmed with multivariate analysis using the Cox proportional hazard model. Radiologically, most grade 3 tumors exhibit a solid nodular pattern on computed tomography images and a high maximum standardized uptake value with positron emission tomography. Genotypically, 43% of the grade 3 adenocarcinomas lacked any driver mutations, although one of the driver mutations was detected in 79% of grade 1 or 2 tumors. Patient age, positive smoking history, solid nodule on computed tomography image, and higher maximum standardized uptake value were identified as significant preoperative predictive factors of grade 3 tumors, with a prediction rate greater than 90%. CONCLUSIONS: Besides stratifying the patient outcomes, the new grading system characterized unique clinicopathologic subsets and this study suggested that grade 3 tumors could be predicted using the preoperative variables.
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Adenocarcinoma del Pulmón , Adenocarcinoma , Neoplasias Pulmonares , Adenocarcinoma/patología , Adenocarcinoma del Pulmón/genética , Adenocarcinoma del Pulmón/patología , Humanos , Neoplasias Pulmonares/patología , Masculino , Estadificación de Neoplasias , Pronóstico , Estudios RetrospectivosRESUMEN
INTRODUCTION: Accurate subtyping of NSCLC into lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) is the cornerstone of NSCLC diagnosis. Cytology samples reveal higher rates of classification failures, that is, subtyping as non-small cell carcinoma-not otherwise specified (NSCC-NOS), as compared with histology specimens. This study aims to identify specific algorithms on the basis of known cytomorphologic features that aid accurate and successful subtyping of NSCLC on cytology. METHODS: A total of 13 expert cytopathologists participated anonymously in an online survey to subtype 119 NSCLC cytology cases (gold standard diagnoses being LUAD in 80 and LUSC in 39) enriched for nonkeratinizing LUSC. They selected from 23 predefined cytomorphologic features that they used in subtyping. Data were analyzed using machine learning algorithms on the basis of random forest method and regression trees. RESULTS: From 1474 responses recorded, concordant cytology typing was achieved in 53.7% (792 of 1474) responses. NSCC-NOS rates on cytology were similar among gold standard LUAD (36%) and LUSC (38%) cases. Misclassification rates were higher in gold standard LUSC (17.6%) than gold standard LUAD (5.5%; p < 0.0001). Keratinization, when present, recognized LUSC with high accuracy. In its absence, the machine learning algorithms developed on the basis of experts' choices were unable to reduce cytology NSCC-NOS rates without increasing misclassification rates. CONCLUSIONS: Suboptimal recognition of LUSC in the absence of keratinization remains the major hurdle in improving cytology subtyping accuracy with such cases either failing classification (NSCC-NOS) or misclassifying as LUAD. NSCC-NOS seems to be an inevitable morphologic diagnosis emphasizing that ancillary immunochemistry is necessary to achieve accurate subtyping on cytology.