A clinicopathologic prediction model for postoperative recurrence in stage Ia non–small cell lung cancer

The Overlooked Cornerstone in Precise Medicine: Personalized Postoperative Surveillance Plan for NSCLC

Non-small cell lung cancer recurrence after curative-intent surgery remains a challenge despite advancements in treatment. We review postoperative surveillance strategies and their impact on overall survival, highlighting recommendations from clinical guidelines and controversies. Studies suggest no clear benefit from more intensive imaging, whereas computed tomography scans reveal promise in detecting recurrence. For early-stage disease, including ground-glass opacities and adenocarcinoma in situ or minimally invasive adenocarcinoma, less frequent surveillance may suffice owing to favorable prognosis. Liquid biopsy, especially circulating tumor deoxyribonucleic acid, holds potential for detecting minimal residual disease. Clinicopathologic factors and genomic profiles can also provide information about site-specific metastases. Machine learning may enable personalized surveillance plans on the basis of multi-omics data. Although precision medicine transforms non-small cell lung cancer treatment, optimizing surveillance strategies remains essential. Tailored surveillance strategies and emerging technologies may enhance early detection and improve patients' survival, necessitating further research for evidence-based protocols.

Nomogram for predicting invasive lung adenocarcinoma in small solitary pulmonary nodules

Background

This study aimed to construct a clinical prediction model and nomogram to differentiate invasive from non-invasive pulmonary adenocarcinoma in solitary pulmonary nodules (SPNs).

Method

We analyzed computed tomography and clinical features as well as preoperative biomarkers in 1,106 patients with SPN who underwent pulmonary resection with definite pathology at Qilu Hospital of Shandong University between January 2020 and December 2021. Clinical parameters and imaging characteristics were analyzed using univariate and multivariate logistic regression analyses. Predictive models and nomograms were developed and their recognition abilities were evaluated using receiver operating characteristic (ROC) curves. The clinical utility of the nomogram was evaluated using decision curve analysis (DCA).

Result

The final regression analysis selected age, carcinoembryonic antigen, bronchus sign, lobulation, pleural adhesion, maximum diameter, and the consolidation-to-tumor ratio as associated factors. The areas under the ROC curves were 0.844 (95% confidence interval [CI], 0.817-0.871) and 0.812 (95% CI, 0.766-0.857) for patients in the training and validation cohorts, respectively. The predictive model calibration curve revealed good calibration for both cohorts. The DCA results confirmed that the clinical prediction model was useful in clinical practice. Bias-corrected C-indices for the training and validation cohorts were 0.844 and 0.814, respectively.

Conclusion

Our predictive model and nomogram might be useful for guiding clinical decisions regarding personalized surgical intervention and treatment options.

Tumor Location Is an Independent Prognostic Factor in Completely Resected Pathological Stage I Non-Small Cell Lung Cancer: A Multicenter Retrospective Study

Previous studies suggested that the location of the primary tumor in non-small cell lung cancer (NSCLC) is associated with clinical features and prognosis, but results are conflicting. The purpose of this study was to explore tumor location as an independent risk factor of survival for patients with completely resected pathological stage I NSCLC. This was a multicenter retrospective study conducted in Taiwan. Included patients were diagnosed with stage I NSCLC and had undergone primary tumor resection. Variables including tumor location, pathological stage, histological differentiation, and International Association for the Study of Lung Cancer (IASLC) grade were evaluated for predictive ability for disease-free survival (DFS) and overall survival (OS). A total of 208 patients were included, with 123 (59.1%) patients having a primary tumor in the upper and middle lobes. The median duration of follow-up for survivors was 60.5 months. Compared to patients with IASLC Grade 3 disease, patients with Grade 1 disease had significantly longer DFS. Tumor location and IASLC grade were independent predictors for OS in multivariate analysis. Specifically, patients with NSCLC in the lower lobe and patients who are histologically classified as IASLC Grade 3 may have poorer prognosis and require greater attention to improve outcomes.

Factors influencing postoperative recurrence of early-stage non-small cell lung cancer

PURPOSE

This study aims to explain the factors that may influence recurrence after surgical resection for early non-small cell lung cancer (NSCLC).

METHODS

A retrospective analysis was made of 302 patients who underwent lung resection for stage I-IIA NSCLC in our clinic between January 2014 and August 2021.

RESULTS

The recurrence rate was higher in patients with squamous cell carcinoma (SCC) than in those with adenocarcinoma (AC) (p = 0.004). Disease-free survival (DFS) was shorter in SCC (p = 0.004). According to histopathological subtypes, the presence of lymphovascular invasion (LVI), vascular invasion (VI), visceral pleural invasion (VPI) and tumor spread through air spaces (STAS) caused an increased risk of recurrence ((p = 0.004), (p = 0.001), (p = 0.047), (p = < 0.001)) and shorter DFS ((p = 0.002), (p = < 0.001), (p = 0.038), (p = < 0.001)). LVI and VI was more common in patients with distant recurrence (p = 0.020, p = 0.002), while the STAS was more common with locoregional recurrence (p = 0.003).

CONCLUSION

The presence of LVI, VI, VPI, and STAS are negative risk factors for recurrence and DFS in all patients and in patients with AC. In patients with SCC, the diagnosis of SCC itself and the presence of STAS were risk factors for recurrence and DFS. Moreover, the risk of distant recurrence is higher in the presence of LVI or VI, and the risk of locoregional recurrence in the presence of STAS is higher.

A nomogram to predict the risk of surgery-related pressure ulcers in patients undergoing cardiovascular surgery

OBJECTIVE

In this study, we aimed to establish a new nomogram score to predict the occurrence of surgery-related pressure ulcers (SRPU) in patients undergoing cardiovascular surgery.

METHODS

We conducted a retrospective study among patients who underwent cardiovascular surgery between February 2016 and November 2020.

RESULTS

We established a prediction model based on a logistic regression model and tested the calibration and discrimination. We included 1163 patients who had undergone cardiovascular surgery. We formulated the logistic regression model, with Logit(P) = -11.745 + 0.024 preoperative hemoglobin value + 0.118 serum sodium value - 0.014 prealbumin value - 0.213 intraoperative mean temperature - 0.058 minimum mean arterial pressure + 0.646 preoperative blood potassium value + 0.264 smoking frequency + 0.760 hypertension history + 0.536 age ≥70 years. In this model ,"+" indicates that the factor is positively related to the occurrence risk of SRPU and "-" indicates that the factor is negatively associated with SRPU risk. The predictive model and nomogram had good accuracy in estimating the risk of SRPU, with a C-index of 0.755 (95% confidence interval: 0.719-0.792).

CONCLUSIONS

The present model can be used to effectively screen patients with a high risk of SRPU to devise targeted nursing intervention strategies and ultimately reduce the incidence rate of SRPU.

Risk factors and prediction model of nomogram for preoperative calf muscle vein thrombosis in geriatric hip fracture patients

Introduction

Calf muscular vein thrombosis (CMVT) is a common complication in geriatric hip fracture patients. Despite its high incidence, prior research on the topic is limited. The occurrence of CMVT in patients will prolong the preoperative waiting time and even lead to serious thromboembolic events, which can be detrimental to the patient's prognosis. Therefore, this study aimed to identify the risk factors for preoperative CMVT in geriatric hip fracture patients and construct a nomogram model to predict the risk of preoperative CMVT in patients.

Materials and methods

Geriatric hip fracture patients who underwent surgery between January 2019 and January 2022 were included. The patients were categorized into two groups depending on whether they had preoperative CMVT, confirmed through Color Doppler ultrasound or venography examination. Univariate and multivariate logistic regression analyses were used to analyze demographic characteristics, medical history, comorbidities, and laboratory tests. A nomogram was constructed to predict preoperative CMVT in geriatric hip fracture patients based on the results of the multivariate logistic regression.

Results

Three hundred and eighty-eight geriatric hip fracture patients, including one hundred and thirty-four patients with CMVT and two hundred and fifty-four patients without CMVT, were ultimately included in our study. After multivariable logistic regression analysis, the time from injury to admission, smoking history, serum albumin levels, and D-dimer levels was identified as independent risk factors and was entered into a nomogram model. The nomogram showed robust discrimination, with an area under the receiver operating characteristic curve of 0.805. The calibration curve showed strong agreement between the CMVT probabilities predicted by the nomogram and the actual probabilities. The decision curve analysis illustrates the excellent clinical utility of the model.

Conclusion

We have constructed a new nomogram prediction model that can effectively predict the risk of preoperative CMVT in geriatric hip fracture patients based on their medical history and blood test results. This model can help clinicians make individualized predictions of CMVT that are tailored to each patient's unique circumstances.

A Nomogram Based on Consolidation Tumor Ratio Combined with Solid or Micropapillary Patterns for Postoperative Recurrence in Pathological Stage IA Lung Adenocarcinoma

BACKGROUND

Patients with pathological stage IA lung adenocarcinoma (LUAD) are at risk of relapse. The value of the TNM staging system is limited in predicting recurrence. Our study aimed to develop a precise recurrence prediction model for stage IA LUAD.

MATERIALS AND METHODS

Patients with pathological stage IA LUAD who received surgical treatment at Zhongshan Hospital Fudan University were retrospectively analyzed. Multivariate Cox proportional hazards regression models were used to create nomograms for recurrence-free survival (RFS). The predictive performance of the model was assessed using calibration plots and the concordance index (C-index).

RESULTS

The multivariate Cox regression analysis revealed that CTR (0.75 < CTR ≤ 1; HR = 9.882, 95% CI: 2.036-47.959, p = 0.004) and solid/micropapillary-predominance (SMPP; >5% and the most dominant) (HR = 4.743, 95% CI: 1.506-14.933, p = 0.008) were independent prognostic factors of RFS. These risk factors were used to construct a nomogram to predict postoperative recurrence in these patients. The C-index of the nomogram for predicting RFS was higher than that of the eighth T-stage system (0.873 for the nomogram and 0.643 for the eighth T stage). The nomogram also achieved good predictive performance for RFS with a well-fitted calibration curve.

CONCLUSIONS

We developed and validated a nomogram based on CTR and SMP patterns for predicting postoperative recurrence in pathological stage IA LUAD. This model is simple to operate and has better predictive performance than the eighth T stage system, making it suitable for selecting further adjuvant treatment and follow-up.

Nomogram Predicting the Prognosis of Patients with Surgically Resected Stage IA Non-small Cell Lung Cancer

The American Joint Committee on Cancer (AJCC) 8th stage system was limited in accuracy for predicting prognosis of stage IA non-small cell lung cancer (NSCLC) patients. This study aimed to establish and validate two nomograms that predict overall survival (OS) and lung cancer-specific survival (LCSS) in surgically resected stage IA NSCLC patients. Postoperative patients with stage IA NSCLC in SEER database between 2004 and 2015 were examined. Survival and clinical information according to the inclusion and exclusion criteria were collected. All patients were randomly divided into the training cohort and validation cohort with a ratio of 7:3. Independent prognosis factors were evaluated using univariate and multivariate Cox regression analyses, and predictive nomogram was established based on these factors. Nomogram performance was measured using the C-index, calibration plots, and DCA. Patients were grouped by quartiles of nomogram scores and survival curves were plotted by Kaplan-Meier analysis. In total, 33,533 patients were included in the study. The nomogram contained 12 prognostic factors in OS and 10 prognostic factors in LCSS. In the validation set, the C-index was 0.652 for predicting OS and 0.651 for predicting LCSS. The calibration curves for the nomogram-predicted probability of OS and LCSS showed good agreement between the actual observation and nomogram prediction. DCA indicated that the clinical value of the nomograms were higher than AJCC 8th stage for predicting OS and LCSS. Nomogram scores related risk stratification revealed statistically significant difference which have better discrimination than AJCC 8th stage. The nomogram can accurately predict OS and LCSS in surgically resected patients with stage IA NSCLC.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13193-022-01700-w.

Clinical characteristics and predictive model of pulmonary tuberculosis patients with pulmonary fungal coinfection

BACKGROUND

In clinical settings, pulmonary tuberculosis (PTB) patients were often found to have pulmonary fungal coinfection. This study aimed to assess the clinical characteristics of patients suffering from coinfection with TB and pulmonary fungal and construct a predictive model for evaluating the probability of pulmonary fungal coinfection in patients with pulmonary tuberculosis.

METHODS

The present case-control study retrospectively collected information from 286 patients affected by PTB who received treatment from December 6,2016- December 6,2021 at Beijing Chest Hospital, Capital Medical University. As control subjects, patients with sex and address corresponding to those of the case subjects were included in the study in a ratio of 1:1. These 286 patients were randomly divided into the training and internal validation sets in a ratio of 3:1. Chi-square test and logistic regression analysis were performed for the training set, and a predictive model was developed using the selected predictors. Bootstrapping was performed for internal validation.

RESULTS

Seven variables [illness course, pulmonary cavitation, broad-spectrum antibiotics use for at least 1 week, chemotherapy or immunosuppressants, surgery, bacterial pneumonia, and hypoproteinemia] were validated and used to develop a predictive model which showed good discrimination capability for both training set [area under the curve (AUC) = 0.860, 95% confidence interval (CI) = 0.811-0.909] and internal validation set (AUC = 0.884, 95% CI = 0.799-0.970). The calibration curves also showed that the probabilities predicted using the predictive model had satisfactory consistency with the actual probability for both training and internal validation sets.

CONCLUSIONS

We developed a predictive model that can predict the probability of pulmonary fungal coinfection in pulmonary tuberculosis patients. It showed potential clinical utility.

Preoperative prognostic prediction for stage I lung adenocarcinomas: Impact of the computed tomography features associated with the new histological grading system

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.

A Nomogram to Predict the Overall Survival of Patients With Resected T1-2N0-1M0 Non-Small Cell Lung Cancer and to Identify the Optimal Candidates for Adjuvant Chemotherapy in Stage IB or IIA Non-Small Cell Lung Cancer Patients

BACKGROUND

The benefit of adjuvant chemotherapy for IB/IIA non-small cell lung cancer (NSCLC) patients remains uncertain. This study aimed to develop a prognostic model to predict overall survival in resected NSCLC patients with T1-2N0-1M0 stage and identify optimal candidates for postoperative chemotherapy among those with stage IB or IIA disease.

METHODS

We conducted a retrospective study using the SEER 18 database (2000-2018, November 2020 submission) of patients who underwent radical surgery for T1-2N0-1M0 NSCLC. The patients not receiving adjuvant chemotherapy were randomly divided into training and validation cohorts. A prognostic nomogram was established and evaluated using calibration and receiver operating characteristic curves. Based on the nomogram, stage IB and IIA patients were categorized into two prognostic groups, each further divided into cohorts based on adjuvant chemotherapy status. Kaplan-Meier analysis and log-rank tests were used to compare overall survival between these groups.

RESULTS

A total of 14 789 patients were enrolled and randomly assigned to the training cohort (n = 10 352) and validation cohort (n = 4437). Ten independent prognostic factors were identified and integrated into the prognostic model. The area under the receiver operating characteristic curve was .706, .699, and .705 in the training cohort, and .700, .698, and .695 in the validation cohort at 1, 3, and 5 years, respectively. Among stage IB and IIA patients, only those in the high-risk group showed a significant benefit from adjuvant chemotherapy, with a 16.4% absolute increase in 5-year overall survival.

CONCLUSIONS

The nomogram developed in the study may help physicians choose the most appropriate management strategy for each patient.

Development and validation of a nomogram for predicting survival time and making treatment decisions for clinical stage IA NSCLC based on the SEER database

Background

The aim of this study was to establish and validate a nomogram model for accurate prediction of patients' survival with T1aN0M0 none small cell lung cancer (NSCLC).

Methods

The patients, diagnosed with the stage IA NSCLC from 2004-2015, were identified from the Surveillance, Epidemiology and End Results (SEER) database. The variables with a P-value < 0.05 in a multivariate Cox regression were selected to establish the nomogram. The discriminative ability of the model was evaluated by the concordance index (C-index). The proximity of the nomogram prediction to the actual risk was depicted by a calibration plot. The clinical usefulness was estimated by the decision curve analysis (DCA). Survival curves were made with Kaplan-Meier method and compared by Log-Rank test.

Results

Eight variables, including treatment, age, sex, race, marriage, tumor size, histology, and grade were selected to develop the nomogram model by univariate and multivariate cox regression. The C-index was 0.704 (95% CI, 0.694-0.714) in the training set and 0.713 (95% CI, 0.697-0.728) in the test set, which performed significantly better than 8th edition AJCC TNM stage system (0.550, 95% CI, 0.408-0.683, P < 0.001). The calibration curve showed that the prediction ability of 3-years and 5-years survival rate demonstrated a high degree of agreement between the nomogram model and the actual observation. The DCA curves also proved that the nomogram-assisted decisions could improve patient outcomes.

Conclusion

We established and validated a prognostic nomogram to predict 3-years and 5-years overall survival in stage IA NSCLC.

Early recurrence factors in patients with stage III non-small cell lung cancer treated with concurrent chemoradiotherapy

BACKGROUND

The clinical characteristics and risk factors for cancer recurrence have not been well evaluated regarding early recurrence in patients with unresectable locally advanced non-small cell lung cancer (LA-NSCLC) who receive concurrent chemoradiotherapy (CRT). The aim of this study was to determine the clinical characteristics and risk factors of patients with stage III unresectable LA-NSCLC treated with CRT who developed early recurrence.

METHODS

We retrospectively reviewed the clinical records of 46 patients diagnosed with stage III unresectable LA-NSCLC treated with CRT at our center between July 2012 and July 2021. A tumor proportion score (TPS) < 50% was defined as "low expression" and a TPS > 50% was defined as "high expression."

RESULTS

A total of 17 (37.0%) patients had a confirmed recurrence within 1 year of treatment. More patients had a lower body mass index in the early recurrence group than in the later recurrence group (p = 0.038). A higher number of patients in the late recurrence group underwent surgery after CRT (p = 0.036). Patients with a higher TPS were more likely to experience late recurrence than early recurrence (p = 0.001), whereas more patients with stage N3 disease were in the early recurrence group (p = 0.011). Multivariate analysis identified lower TPS expression as an independent risk factor for early recurrence after CRT. Overall survival was prolonged in the late recurrence group (p < 0.001).

CONCLUSIONS

A lower TPS may be a predictor of early recurrence after CRT in patients with LA-NSCLC. These patients should be closely monitored for post-treatment recurrence.

A nomogram model of postoperative prognosis for metastatic lung adenocarcinoma: A study based on the SEER database

We have observed that patients with metastatic lung adenocarcinoma can obtain survival benefits from surgical resection of the primary tumor. A model was developed to evaluate the prognosis of patients. The patients with metastatic lung adenocarcinoma were identified in the Surveillance, Epidemiology, and End Results database and divided into surgery group and non-surgical group. Through Kaplan-Meier analysis, the survival rate of the non-surgical group was found to be significantly lower no matter before or after propensity score matching. One thousand one hundred and seventy surgical patients were divided into a training group and a verification group. In the training group, univariate and multivariate Cox models were used to explore the prognostic factors, and logistic regression was used to establish a nomogram based on significant predictors. In total, 12,228 patients with metastatic lung adenocarcinoma were recognized; primary tumor surgery accounted for 9.5%. After propensity score matching, the median survival time of 2 groups was significantly different. For the training group, univariate and multivariate COX analysis was conducted, and a nomogram was constructed. Acceptable agreement has been achieved between the predicted and observed survival rates, and the nomogram can divide patients with metastatic lung adenocarcinoma into different risk groups and predict their prognostic survival rate.

[A Review on Pathological High-risk Factors and Postoperative Adjuvant Chemotherapy in Stage IA Lung Adenocarcinoma]

The survival rate needs to be improved in early stage non-small cell lung cancer patients. The risk of recurrence is relatively high in invasive adenocarcinoma patients with a solid or micropapillary component, lymphovascular invasion or tumor spread through air spaces. Systemic treatment options including radical surgical resection should be explored for this population. Adjuvant chemotherapy is not recommended for patients in stage IA in current guidelines. This article is a review on the research progress of the above pathological high-risk factors and the role of adjuvant chemotherapy in patients with pathological high-risk factors in stage IA lung adenocarcinoma.
.

Effect of Adjuvant Chemotherapy on Survival of Patients With 8th Edition Stage IB Non-Small Cell Lung Cancer

BACKGROUND

The efficacy of adjuvant chemotherapy in patients with 8th edition stage IB (tumor size ≤4 cm) non-small cell lung cancer (NSCLC) remains unclear.

METHODS

We identified 9757 eligible patients (non-chemotherapy group: n=8303; chemotherapy group: n=1454) between 2004 and 2016 from the Surveillance, Epidemiology and End Results (SEER) database. Log-rank test was used to compare overall survival (OS) between the chemotherapy and non-chemotherapy groups. Cox regression model was applied to investigate the independent prognosis factors of all surgically treated stage IB patients, and then the nomogram was constructed. Propensity score matching (PSM) was performed to reduce the confounding bias, and subgroup analyses of the matched cohort were also performed. Finally, we reviewed 184 patients with stage IB NSCLC from July 2008 to December 2016 in Jinling Hospital as a validation cohort, and compared disease-free survival (DFS) and OS between the two groups.

RESULTS

In the SEER database cohort, adjuvant chemotherapy was associated with improved OS in both unmatched and matched (1417 pairs) cohorts (all P <0.05). The survival benefit (both OS and DFS) was confirmed in the validation cohort (P <0.05). Multivariate analysis showed age, race, sex, marital status, histology, tumor location, tumor size, differentiation, surgical method, lymph nodes (LNs) examined, radiotherapy and chemotherapy were prognostic factors for resected stage IB NSCLC (all P <0.05). The concordance index and calibration curves demonstrated good prediction effect. Subgroup analyses showed patients with the following characteristics benefited from chemotherapy: old age, poor differentiation to undifferentiation, 0-15 LNs examined, visceral pleural invasion (VPI), lobectomy and no radiotherapy (all P <0.05).

CONCLUSIONS

Adjuvant chemotherapy is associated with improved survival in 8th edition stage IB NSCLC patients, especially in those with old age, poorly differentiated to undifferentiated tumors, 0-15 LNs examined, VPI, lobotomy and no radiotherapy. Further prospective trials are needed to confirm these conclusions. Besides, the nomogram provides relatively accurate prediction for the prognosis of resected stage IB NSCLC patients.

Oncogenic Alterations in Histologically Negative Lymph Nodes Are Associated with Prognosis of Patients with Stage I Lung Adenocarcinoma

Simple Summary

Lymph nodes (LNs) metastasis is one of the most important factors affecting the outcome of non-small cell lung. The aim of this study is to explore whether presence of oncogenic alterations in histologically-negative lymph nodes (LNs) can be of prognostic significance in stage I lung adenocarcinoma (LUAD). We confirmed that presence of oncogenic alterations in regional LN may be associated with higher risks of postsurgical recurrence of Stage I LUAD, particularly for certain molecular subgroups. These results warranted future studies on larger cohort of NSCLC patients using more comprehensive cancer gene panels to establish the clinical impact of molecular LN occult metastasis for localized NSCLC and identify Stage I patients at high risks for recurrence for appropriate adjuvant therapy.

Abstract

Background: Survival of patients with stage I non-small cell lung cancer (NSCLC) varies greatly. We sought to explore whether presence of oncogenic alterations in histologically-negative lymph nodes (LNs) can be of prognostic significance in stage I lung adenocarcinoma (LUAD). Methods: Genomic analysis of oncogenic alterations was applied to 123 stage I LUAD tumors. The same genomic variants identified in primary tumors were examined in corresponding histologically-negative LNs. Results: A total of 102 (82.9%) patients had at least one canonical oncogenic alteration detected in primary tumors, and 57 LNs from 12 patients (11.8%) were found to carry the identical oncogenic alterations detected in the corresponding primary tumor tissues, including EGFR mutations (six cases), KRAS mutations (three cases), ALK fusion (one case), BRAF mutation (one case) and HER2 & NRAS co-mutations (one case). None of these LNs was found to have occult tumor cells by routine pathological assessment or immunohistochemistry staining using antibodies against pan-cytokeratins (AE1/AE3) and the epithelial marker Ber-EP4. The detection rate of oncogenenic alterations in LN was significantly higher in RAS-mutant tumors than EGFR mutant tumors (36.36% verse 7.41%, p = 0.017). Patients with oncogenic alterations in LN showed inferior disease-free survival (DFS, p = 0.025) and overall survival (OS, p = 0.027). Furthermore, patients with RAS-mutations detected in LN had the worst DFS and OS (p = 0.001). Among the 11 patients with RAS mutation in primary tumors, DFS and OS in the four patients with mutations detected in LN were significantly shorter than the remaining seven patients without mutations LN (DFS, p = 0.001, OS, p = 0.002). Conclusions: Genomic analysis has the potential to detect oncogenic alterations in regional LNs for localized LUAD and presence of oncogenic alterations in regional LN may be associated with inferior clinical outcome of stage I LUAD, particularly for certain molecular subgroups. ClinicalTrials.gov ID NCT04266691

Risk factors of prolonged ventilation after thymectomy in thymoma myasthenia gravis patients

BACKGROUND

To explore the risk factors for prolonged ventilation after thymectomy in patients with thymoma associated with myasthenia gravis (TAMG).

METHODS

We reviewed the records of 112 patients with TAMG after thymectomy between January 2010 and December 2019 in Peking University People's Hospital. Demographic, pathological, preoperative data and the Anesthesia, surgery details were assessed with multivariable logistic regression analysis to predict the risk of prolonged ventilation after thymectomy. A nomogram to predict the probability of post-thymectomy ventilation was constructed with R software. Discrimination and calibration were employed to evaluate the performance of the nomogram.

RESULTS

By multivariate analysis, male, low vital capacity (VC), Osserman classification (IIb, III, IV), total intravenous anesthesia, and long operation time were identified as the risk factors and entered into the nomogram. The nomogram showed a robust discrimination, with an area under the receiver operating characteristic curve (AUC) of 0. 835 (95% confidence interval [CI], 0.757-0.913). The calibration plot indicated that the nomogram-predicted probabilities compared very well with the actual probabilities (Hosmer-Lemeshow test: P = 0.921).

CONCLUSION

The nomogram is a valuable predictive tool for prolonged ventilation after thymectomy in patients with TAMG.

Prognostic Value of Inflammatory Biomarkers in Patients With Stage I Lung Adenocarcinoma Treated With Surgical Dissection

Objective

Inflammation plays a crucial role in tumorigenesis and progression. Our purpose was to investigate the prognostic value of neutrophil-to-lymphocyte ratio (NLR), systemic inflammation response index (SIRI) and systemic immune-inflammation index (SII), and develop a nomogram to predict the cancer-specific survival (CSS) and disease-free survival (DFS) of stage I lung adenocarcinoma patients.

Methods

1431 patients undergoing surgical resection with pathologically confirmed stage I lung adenocarcinoma were reviewed. The optimal cut-off values for NLR, SII, and SIRI were defined by the receiver operating characteristic (ROC) curve. Cox proportional hazards regression analyses were performed to recognize factors significantly correlated with CSS and DFS to construct the nomogram. The value of adjuvant chemotherapy on model-defined high-risk and low-risk patients was further explored.

Results

The cohort had a median follow-up time of 63 months. Multivariate analysis revealed that higher NLR (≥2.606), higher SIRI (≥0.705), higher SII (≥580.671), later T stage, histological pattern with solid or micropapillary components and radiologic features with solid nodules were significantly associated with worse CSS and DFS. The concordance index (C-index) of the nomogram established by all these factors was higher than that of the TNM staging system both in CSS (validation set 0.778 vs 0.652) and DFS (validation set 0.758 vs 0.695). Furthermore, the value of the established nomogram on risk stratification in stage I lung adenocarcinoma patients was validated.

Conclusions

Higher NLR, SII and SIRI pretreatment were associated with worse survival outcomes. A practical nomogram based on these three inflammatory biomarkers may help clinicians to precisely stratify stage I lung adenocarcinoma patients into high- and low-risk and implement individualized treatment.

Recurrence and disease-free survival outcomes after computed tomography-guided needle biopsy in stage IA non-small cell lung cancer patients in China: a propensity score matching analysis

Background

Whether preoperative biopsy before radical resection can lead to recurrence and impact patient survival in non-small cell lung cancer (NSCLC) remains controversial. In this study, we carried out a retrospective analysis to determine whether preoperative biopsy can cause disease recurrence and influence disease-free survival (DFS) in patients with stage IA NSCLC.

Methods

Patients diagnosed with stage IA NSCLC (solid nodule) between January 2010 and December 2014 were identified from the databases of 7 Chinese medical centers and divided into two groups: a preoperative computed tomography (CT)-guided needle biopsy (CTNB) plus radical resection group, and a non-CTNB group. The propensity score matching (PSM) method was adopted to balance the observed covariates, and Kaplan-Meier estimates were used for survival analysis. Cox regression was used in a single-factor analysis to identify the factors affecting DFS in stage IA NSCLC.

Results

After initial screening, 730 patients were enrolled in this study, with 186 and 544 patients in the CTNB group and the non-CTNB group, respectively. After PSM, 186 patients were eventually included in each group. No significant differences in basic clinical features were identified between the two groups (P>0.05). The rates of recurrence were 17.2% and 14.0% in the CTNB and non-CTNB groups (χ²=0.735, P=0.391), respectively. No notable differences in DFS (χ²=1.895, P=0.173) or overall survival (OS, χ²=1.785, P=0.182) were observed. Lung adenocarcinoma [hazard ratio (HR), 0.167, P=0.001] and lesion size (>2 cm) (HR, 2.712, P=0.000) were identified as risk factors for DFS in stage IA NSCLC.

Conclusions

CTNB does not increase the incidence of recurrence in stage IA NSCLC or affect patient survival; therefore, it is not a risk factor for DFS. Lung adenocarcinoma and lesion size are risk factors for DFS.

Overall Survival Analyses following Adjuvant Chemotherapy or Nonadjuvant Chemotherapy in Patients with Stage IB Non-Small-Cell Lung Cancer

Background

Adjuvant chemotherapy (ACT) can improve prognosis for stages II-IIIA patients with non-small-cell lung cancer (NSCLC), but its implication in stage I patients is still an intractable puzzle. This study aims to seek ACT candidates for stage IB NSCLC and establish a nomogram to predict overall survival (OS) of specific patient for clinician's decision.

Method

We performed a retrospective study on 16,765 patients (ACT group: n = 2,187; non-ACT group: n = 14,578) from the Surveillance, Epidemiology, and End Results (SEER) database. Overall survival was assessed in two groups. We performed propensity-score matching for risk adjustment. The risk factors were identified and used to create nomogram. Concordance index (C-index), Hosmer–Lemeshow test, and calibration were applied to evaluate model performance. To further evaluate the influence of tumor size on the selection of potential ACT candidates for patients with stage IB NSCLC, subgroup analyses were executed.

Result

Survival analysis for the entire study cohort showed that ACT had better OS than non-ACT (HR = 0.800, CI: (0.751–0.851), P < 0.0001). In matched cohort, ACT also presented better OS than non-ACT (HR = 0.775, CI: (0.704–0.853), P < 0.0001). Univariate and multivariate Cox regression analysis revealed that eight prognostic factors, including gender, age, grade, pathological subtype, tumor size, visceral pleural invasion, surgical procedure, and the number of removed lymph nodes, were significantly correlated with OS. The nomogram was further constructed based on these prognostic factors. The C-index of nomogram was 0.639 (95%CI: 0.632–0.646). The Hosmer–Lemeshow test, and calibration presented good congruence between the predictions and actual observations. Subgroup analyses of tumor size group showed that ACT shared similar OS to non-ACT in NSCLC patients with tumor size ≤20 mm (P > 0.05). However, for NSCLC patients with 20 mm < size ≤30 mm (HR = 0.845, 95%CI (0.724–0.986), P=0.032) and 30 mm < size ≤40 mm (HR = 0.912, 95%CI (0.833–1.000), P=0.049), ACT associated with better OS.

Conclusion

In this study, we found that ACT had better OS than non-ACT in patients with stage IB NSCLC. The nomogram provided an individual prediction of OS for patients after surgical resection. Patients with tumor size >20 mm and ≤40 mm may be potential candidates for ACT.

Nomogram to Predict Cancer Specific Survival in Patients with Pathological Stage IA Non-small Cell Lung Cancer

We identified the prognostic factors of resected stage IA non-small cell lung cancer (NSCLC) and developed a nomogram, with purpose of defining the high-risk population who may need closer follow-up or more intensive care. Eligible stage IA NSCLC cases from the Surveillance, Epidemiology, and End Results (SEER) database and the Sun Yat-sen University Cancer Center (SYSUCC) were included. Stage IB NSCLCs were also included for evaluating the risk stratification efficacy. Cancer specific survival (CSS) was compared between groups. Statistically significant factors from multivariate analysis were entered into the nomogram. The performance of the nomogram was evaluated by concordance index (C-index) and calibration plots. A total of 23,112 NSCLC cases (SEER stage IA training cohort, N=7,777; SEER stage IA validation cohort, N=7,776; SEER stage IB cohort, N=7,559) from the SEER database were included. 1,304 NSCLC cases (SYSUCC stage IA validation cohort, N=684; SYSUCC stage IB cohort, N=620) from the SYSUCC were also included. Younger age, female, lobectomy, well differentiated, smaller size and more examined lymph nodes were identified as favorable prognostic factors. A nomogram was established. The C-index was 0.68 (95%CI, 0.67-0.69), 0.66 (95% CI, 0.64-0.68) and 0.66 (95% CI, 0.61-0.71) for the SEER training cohort, SEER validation cohort and SYSUCC validation cohort. A risk classification system was constructed to stratify stage IA NSCLC into low-risk subgroup and high-risk subgroup. The CSS curves of these two subgroups showed statistically significant distinctions. This nomogram delivered a prognostic prediction for stage IA NSCLC and may aid individual clinical practice.

Tumor Differentiation and EGFR Mutation Associated with Disease-Free Survival in Stage IA Lung Adenocarcinoma Patients with Curative Surgery

Background

Nearly 30% of stage IA non-small-cell lung cancer patients eventually die of recurrence or metastasis. This study aimed to predict stage IA lung adenocarcinoma (LADC) patients who underwent radical resection with a high risk of recurrence or metastasis.

Methods

Information on clinicopathological, genetic and therapeutic features and recurrence status was collected in this retrospective and two-center study. A nomogram based on multivariate analysis was established to predict disease-free survival. Further stratification was performed to identify populations with a high risk of relapse.

Results

A total of 1584 patients with pathological stage IA LADC who underwent radical surgery between 2011 and 2015 were enrolled from two medical institutions in this study. The nomogram including tumor differentiation and EGFR mutation had a higher C-index of 0.880 (95% CI 0.833–0.926) compared to 0.598 (95% CI 0.486–0.711) for the AJCC 8th TNM staging system. Furthermore, the C-index for the validation cohort was 0.798 (95% CI 0.738–0.857). In addition, the 3-year cumulative nonrecurrence rate in the high-risk group stratified by this model was 21.8% compared to 98.1% in the low-risk group.

Conclusion

This study proposed a new nomogram including tumor differentiation and EGFR mutation to predict recurrence or metastatic probability in stage IA LADC patients who underwent radical surgery. This nomogram could identify patients in the high-risk group and help guide adjuvant treatment in the future.

New International Association for the Study of Lung Cancer (IASLC) Pathology Committee Grading System for the Prognostic Outcome of Advanced Lung Adenocarcinoma

Simple Summary

This study investigated the association between survival outcome and the new grading system among advanced stage lung adenocarcinoma (LADC) (stages IIIA, IIIB and IV) patients who were diagnosed as LADC with a pathologic report according to a new grading system by the International Association for the Study of Lung Cancer (IASLC) pathology committee. The results indicate that the poorly differentiated group had a poorer prognosis in PFS, as did patients with wild-type EGFR who were treated with chemotherapy. No survival difference could be found among EGFR mutation patients. Older age and a lower body mass index also led to worse survival. Patients with poorly differentiated adenocarcinoma likewise had worse survival, especially compared to those with moderately differentiated adenocarcinoma. Our findings highlight that the therapeutic regimen should be adjusted for wild-type EGFR patients with poorly differentiated adenocarcinoma treated with chemotherapy to provide better outcomes. No survival difference could be seen among EGFR mutation patients.

Abstract

The impact of the new International Association for the Study of Lung Cancer pathology committee grading system for advanced lung adenocarcinoma (LADC) on survival is unclear, especially in Asian populations. In this study, we reviewed the prognostic outcomes of patients with late-stage disease according to the new grading system. We reviewed 136 LADC cases who underwent a small biopsy from 2007 to 2018. Tumors were classified according to the new grading system for LADC. Baseline characteristics (age, sex, smoking status, body mass index, and driver gene mutations) were analyzed. Kaplan–Meier and Cox regression analyses were used to determine correlations with the new grading system and prognosis. Patients with poorly differentiated adenocarcinoma were significantly correlated with a poor progression-free survival (PFS) (p = 0.013) but not overall survival (OS) (p = 0.154). Subgroup analysis showed that wild-type EGFR patients with poorly differentiated adenocarcinoma treated with chemotherapy had significantly worse PFS (p = 0.011). There was no significant difference in survival among the patients with epidermal growth factor receptor mutations who were treated with tyrosine kinase inhibitors. Patients aged >70 years and those with a BMI ≤ 25 kg/m² and wild-type patients had significantly worse OS in both univariate (HR = 1.822, p = 0.006; HR = 2.250, p = 0.004; HR = 1.537, p = 0.046, respectively) and multivariate analyses (HR = 1.984, p = 0.002; HR = 2.383, p = 0.002; HR = 1.632, p = 0.028, respectively). Despite therapy, patients with poorly differentiated tumors still fared worse than those with better differentiated tumors. No differences were found among the EGFR mutations treated with TKI. Our findings highlight that the therapeutic regimen should be adjusted for EGFR Wild-type patients with poorly differentiated adenocarcinoma treated with chemotherapy to provide better outcomes.

Nomograms for Predicting Overall and Recurrence-free Survival From Pathologic Stage IA and IB Lung Cancer After Lobectomy

BACKGROUND

Stage I non-small-cell lung cancer (NSCLC) is potentially curable with surgical resection. Significant proportions of patients may still experience recurrence and death despite undergoing curative surgery. This study describes predictive nomograms for recurrence-free (RFS) and overall survival (OS) after lobectomy.

PATIENTS AND METHODS

A total of 301 patients with the American Joint Committee on Cancer pathologic stage IA and IB NSCLC who underwent open, thoracoscopic, or robotic lobectomy from January 2011 to April 2017 were analyzed. Multivariate Cox proportional hazards regression models were used to create nomograms for OS and RFS. Kaplan-Meier survival curves were calculated for OS and RFS comparing high-risk and low-risk cohorts based on nomogram scores.

RESULTS

Histology (hazard ratio [HR], 0.24; 95% confidence interval [CI], 0.10-0.56; P = .002), lymphovascular invasion (HR, 0.46; 95% CI, 0.29-0.74; P = .001), smoking status (HR, 3.46; 95% CI, 1.25-9.55: P = .02), and total lymph nodes removed (HR, 1.05; 95% CI, 1.01-1.10; P = .021) were significant predictors for OS in a multivariate model. Lymphovascular invasion (HR, 0.55; 95% CI, 0.36-0.83; P = .0040), smoking status (HR, 2.56; 95% CI, 1.16-5.62; P = .02), total lymph nodes removed (HR, 1.04; 95% CI, 1.00-1.08; P = .029), and tumor size (HR, 1.30; 95% CI, 1.30-1.68; P = .047) were significant predictors of RFS in a multivariate model.

CONCLUSION

Nomograms can predict OS and RFS for pathologic stage IA and IB NSCLC after lobectomy regardless of operative approach. The risk for death and recurrence after stratification by the nomogram scores may provide guidance regarding adjuvant therapy and surveillance.

A nomogram based on a patient-reported outcomes measure: predicting the risk of readmission for patients with chronic heart failure

BACKGROUND

Health-related quality of life, as evaluated by a patient-reported outcomes measure (PROM), is an important prognostic marker in patients with chronic heart failure. This study aimed to use PROM to establish an effective readmission nomogram for chronic heart failure.

METHODS

Using a PROM as a measurement tool, we conducted a readmission nomogram for chronic heart failure on a prospective observational study comprising of 454 patients with chronic heart failure hospitalized between May 2017 to January 2020. A Concordance index and calibration curve were used to evaluate the discriminative ability and predictive accuracy of the nomogram. A bootstrap resampling method was used for internal validation of results.

RESULTS

The median follow-up period in the study was 372 days. After a final COX regression analysis, the gender, income, health care, appetite-sleep, anxiety, depression, paranoia, support, and independence were identified and included in the nomogram. The nomogram showed moderate discrimination, with a concordance index of 0.737 (95% CI 0.673-0.800). The calibration curves for the probability of readmission for patients with chronic heart failure showed high consistency between the probability, as predicted, and the actual probability.

CONCLUSIONS

This model offers a platform to assess the risk of readmission for different populations with CHF and can assist clinicians with personalized treatment recommendations.

The prognostic value of a Methylome-based Malignancy Density Scoring System to predict recurrence risk in early-stage Lung Adenocarcinoma

Current NCCN guidelines do not recommend the use of adjuvant chemotherapy for stage IA lung adenocarcinoma patients with R0 surgery. However, 25% to 40% of patients with stage IA disease experience recurrence. Stratifying patients according to the recurrence risk may tailor adjuvant therapy and surveillance imaging for those with a higher risk. However, prognostic markers are often identified by comparing high-risk and low-risk cases which might introduce bias due to the widespread interpatient heterogeneity. Here, we developed a scoring system quantifying the degree of field cancerization in adjacent normal tissues and revealed its association with disease-free survival (DFS).

Methods: We recruited a cohort of 44 patients with resected stage IA lung adenocarcinoma who did not receive adjuvant therapy. Both tumor and adjacent normal tissues were obtained from each patient and subjected to capture-based targeted genomic and epigenomic profiling. A novel methylome-based scoring system namely malignancy density ratio (MD ratio) was developed based on 39 patients by comparing tumor and corresponding adjacent normal tissues of each patient. A MD score was then obtained by Wald statistics. The correlations of MD ratio, MD score, and genomic features with clinical outcome were investigated.

Results: Patients with a high-risk MD ratio showed a significantly shorter postsurgical DFS compared with those with a low-risk MD ratio (HR=4.47, P=0.01). The MD ratio was not associated with T stage (P=1), tumor cell fraction (P=0.748) nor inflammatory status (p=0.548). Patients with a high-risk MD score also demonstrated an inferior DFS (HR=4.69, P=0.039). In addition, multivariate analysis revealed EGFR 19 del (HR=5.39, P=0.012) and MD score (HR= 7.90, P=0.01) were independent prognostic markers.

Conclusion: The novel methylome-based scoring system, developed by comparing the signatures between tumor and corresponding adjacent normal tissues of individual patients, largely minimizes the bias of interpatient heterogeneity and reveals a robust prognostic value in patients with resected lung adenocarcinoma.

Clinicopathologic Features and Genetic Alterations in Adenocarcinoma In Situ and Minimally Invasive Adenocarcinoma of the Lung: Long-Term Follow-Up Study of 121 Asian Patients

BACKGROUND

Adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) are both small tumors with good prognosis after surgical resection, and most of them present as ground glass opacities (GGOs) on computed tomography (CT) screening. However, the differences in clinicopathologic features and genetic alterations between AIS and MIA are poorly elaborated, and few studies have evaluated the prognosis of MIA with different invasive components. Meanwhile, the histological features of lung lesions presenting as unchanged pure GGOs are barely understood.

METHODS

Clinicopathologic features and genetic alterations of AIS (n = 59) and MIA (n = 62) presenting as GGOs were analyzed. Long-term preoperative observation (ranging from 2 to 1967 days) and postoperative follow-up (ranging from 0 to 92 months) was conducted.

RESULTS

The tumor size and consolidation/tumor ratio were significantly larger in the MIA cohort than those in the AIS cohort both on CT and microscopy images. Immunohistochemically, the expression of p53, Ki67, and cyclin D1 was higher in MIA than in AIS. The EGFR mutation rate was significantly higher in MIA, while other genetic alterations showed no differences. Six MIA cases showed recurrence or metachronous adenocarcinoma and all the cases with a predominant micropapillary invasive pattern demonstrated this feature.

CONCLUSIONS

The current CT measurements may be helpful in distinguishing AIS from MIA, but show limited utility in predicting the histology of unchanged pure GGOs. The invasive pattern may have an influence on the postoperative process of MIA; therefore, further studies are needed to evaluate the current diagnostic criteria and treatment strategy for MIA.

Development and External Validation of a Nomogram for Predicting Survival in Patients With Stage IA Non-small Cell Lung Cancer ≤2 cm Undergoing Sublobectomy

Background: Postoperative prognosis of early stage non-small cell lung cancer (NSCLC) undergoing sublobectomy is heterogeneous. Therefore, we sought to construct a novel survival prediction model for stage IA NSCLC ≤2 cm undergoing sublobectomy.

Methods: Based on the data from the Surveillance, Epidemiology, and End Results (SEER) program, we successfully determined and incorporated independent prognostic markers to construct the nomogram. Internal validation of the constructed nomogram was conducted through 1,000 bootstrap resamples. The constructed nomogram was further subjected to external validation with an independent cohort of patients from two Chinese institutions. The performance of the survival prediction model was assessed by concordance index, calibration plots, and risk subgroup classification.

Results: A total of 3,238 patients from SEER registries (development cohort), as well as 769 patients from two Chinese institutions (validation cohort) was included. Gender, age, size, histologic type, grade, and examined lymph nodes count were identified as significant prognostic parameters. A novel nomogram was developed and externally validated. Concordance index of constructed nomogram was significantly better than that of the current TNM staging system. Calibration plots demonstrated an optimal consistency between the nomogram predicted and actual observed probability of survival. Survival curves of different risk subgroups within respective TNM stage demonstrated significant distinctions.

Conclusion: We developed and externally validated a survival prediction model for patients with stage IA NSCLC ≤2 cm undergoing sublobectomy. This novel nomogram outperforms the conventional TNM staging system and could help clinicians in postoperative surveillance and future clinical trial design.

A nomogram to predict overall survival of patients with early stage non-small cell lung cancer

Background

Nomograms have been widely used for estimating cancer prognosis. The aim of this study was to construct a clinical nomogram that would well predict overall survival of early stage non-small cell lung cancer (NSCLC) patients after surgery resection.

Methods

A total of 443 patients diagnosed with pathologic stage I and II NSCLC who had undergone curative resection without neoadjuvant chemotherapy or radiotherapy were recruited and analyzed. The log-rank test and multivariate Cox regression analysis were used to select the most significant predictors in the final nomogram for predicting overall survival. Furthermore, the model was validated by bootstrap methods and measured by concordance index (C-index) and calibration plots.

Results

Four independent predictors for overall survival were identified and included into the delineation of the nomogram (tumor differentiation, station of sampled lymph nodes, pathologic T and pathologic N). The model showed comparatively stable discrimination (bootstrap-corrected C-index =0.622, 95% CI: 0.572-0.672) and good calibration.

Conclusions

We successfully developed a nomogram incorporating available clinicopathological variables to predict overall survival of early stage NSCLC patients after surgery resection, which might help clinician select better appropriate treatment decisions.

Adjuvant Chemotherapy Candidates in Stage I Lung Adenocarcinomas Following Complete Lobectomy

BACKGROUND

This study aimed to explore adjuvant chemotherapy (ACT) candidates based on a recurrence risk-scoring model in completely lobectomized stage I patients with lung adenocarcinoma (LAD).

METHODS

A retrospective study was performed on 4606 patients (non-ACT group: n = 3514; ACT group: n = 1092) who underwent complete lobectomy for LAD at Shanghai Chest Hospital from 2008 to 2014. The nomogram predicting recurrence-free survival (RFS) was developed in the non-ACT group using Cox proportional hazards regression. The nomogram-based risk score was calculated in the entire cohort. Differences of RFS between the non-ACT and ACT groups were compared as stratified by the risk score. The score cut-off points were determined using the X-tile software.

RESULTS

Six independent predictors, including age, sex, tumor size, pathological subtype, visceral pleural invasion (VPI), and lymphovascular invasion (LVI) were associated with RFS. The nomogram more accurately predicted RFS than the 8th TNM staging {C-index: 0.784 [95% confidence interval (CI) 0.756-0.812] vs. 0.719 (95% CI 0.689-0.749), p = 0.0017}. A significant RFS difference was observed among the low-, intermediate- and high-risk groups (p < 0.0001), as divided by the optimal cut-points of risk score (203 and 244). ACT did not improve RFS for patients at intermediate-risk, or was even detrimental for low-risk patients; however, improved RFS was observed in ACT receivers at high-risk (p = 0.0416). ACT candidates with a risk score ≥ 245 constituted 2.6% of stage I patients.

CONCLUSIONS

The nomogram provided an individual prediction of RFS for stage I LAD following lobectomy. High-risk patients (score ≥ 245) may benefit from postoperative ACT.

A Nomogram for Predicting Cancer-Specific Survival of TNM 8th Edition Stage I Non-small-cell Lung Cancer

BACKGROUND

Models for predicting the survival outcomes of stage I non-small-cell lung cancer (NSCLC) defined by the newly released 8th edition TNM staging system are scarce. This study aimed to develop a nomogram for predicting the cancer-specific survival (CSS) of these patients and identifying individuals with a higher risk for CSS.

METHODS

A total of 30,475 NSCLC cases were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. We identified and integrated the risk factors to build a nomogram. The model was subjected to bootstrap internal validation with the SEER database, and external validation with a multicenter cohort of 1133 patients from China. The difference in the impact of adjuvant chemotherapy on model-defined high- and low-risk patients was examined using the National Cancer Database (NCDB).

RESULTS

Eight independent prognostic factors were identified and integrated into the model. The calibration curves showed good agreement. The concordance index (C-index) of the nomogram was higher than that of the staging system (IA1, IA2, IA3, and IB) (internal validation set 0.63 vs. 0.56; external validation set 0.66 vs. 0.55; both p < 0.01). Specifically, 21.7% of stage IB patients (7.5% of all stage I) were categorized into the high-risk group (score > 30). There was a significant interaction effect between the adjuvant chemotherapy and risk groups in the NCDB cohort (p = 0.003).

CONCLUSIONS

We established a practical nomogram to predict CSS for 8th edition stage I NSCLC. A prospective study is warranted to determine its role in identifying adjuvant chemotherapy candidates.

Procedure-Specific Risk Prediction for Recurrence in Patients Undergoing Lobectomy or Sublobar Resection for Small (≤2 cm) Lung Adenocarcinoma: An International Cohort Analysis

INTRODUCTION

This work was performed to develop and validate procedure-specific risk prediction for recurrence following resection for early-stage lung adenocarcinoma (ADC) and investigate risk prediction utility in identifying patients who may benefit from adjuvant chemotherapy (ACT).

METHODS

In patients who underwent resection for small (≤2 cm) lung ADC (lobectomy, 557; sublobar resection, 352), an association between clinicopathologic variables and risk of recurrence was assessed by a competing risks approach. Procedure-specific risk prediction was developed based on multivariable regression for recurrence. External validation was conducted using cohorts (N = 708) from Japan, Taiwan, and Germany. The accuracy of risk prediction was measured using a concordance index. We applied the lobectomy risk prediction approach to a propensity score-matched cohort of patients with stage II-III disease (n = 316, after matching) with or without ACT and compared lung cancer-specific survival between groups among low- or high-risk scores.

RESULTS

Micropapillary pattern, solid pattern, lymphovascular invasion, and necrosis were involved in the risk prediction following lobectomy, and micropapillary pattern, spread through air spaces, lymphovascular invasion, and necrosis following sublobar resection. Both internal and external validation showed good discrimination (concordance index in lobectomy and sublobar resection: internal, 0.77 and 0.75, respectively; and external, 0.73 and 0.79, respectively). In the stage II-III propensity score-matched cohort, among high-risk patients, ACT significantly reduced the risk of lung cancer-specific death (subhazard ratio 0.43, p = 0.001), but not among low-risk patients.

CONCLUSIONS

Procedure-specific risk prediction for patients with resected small lung ADC can be used to better prognosticate and stratify patients for further interventions.

Genetic analyses of differences between solid and nonsolid predominant lung adenocarcinomas

BACKGROUND

Solid predominant lung adenocarcinomas (LUAD) have distinct histopathological and clinical characteristics compared with nonsolid subtypes. A comprehensive comparison of altered genes found in solid and nonsolid subtypes has not previously been performed. In this study, we analyzed differences in gene expression, genetic mutations, and DNA methylation to better understand the risk factors for these two subtypes of LUAD.

METHODS

Differentially expressed genes (DEGs) and differentially mutated genes (DMGs) were analyzed from RNA-seq data downloaded from The Cancer Genome Atlas (TCGA) and Broad Institute database. To understand the functional significance of molecular changes, we examined the DEGs and DMGs with Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis.

RESULTS

A total of 184 patients in the TCGA cohort and 140 patients in the Broad Institute cohort were included in this study. We identified 75 DEGs, of which 15 were upregulated and 56 downregulated in the solid group relative to the nonsolid group. The DEGs were mainly involved in the regulation of water and fluid transport. We discovered 38 significantly differentially expressed genes that overlapped in the two groups. The DMGs were mainly enriched for pathways involved in cell-cell adhesion, cell adhesion, biological adhesion, and hemophilic cell adhesion. We additionally discovered nine significantly methylated genes between solid and nonsolid LUAD.

CONCLUSIONS

Our study identified distinct DEGs, DMGs, and methylation genes for solid and nonsolid LUAD subtypes. These findings improve our understanding of the different carcinogenesis mechanisms in LUAD and will help to develop new therapeutic strategies.

Challenges in Predicting Recurrence After Resection of Node-Negative Non-Small Cell Lung Cancer

BACKGROUND

One in 5 patients with completely resected early-stage non-small cell lung cancer will recur within 2 years. Risk stratification may facilitate a personalized approach to the use of adjuvant therapy and surveillance imaging. We developed a prediction model for recurrence based on five clinical variables (tumor size and grade, visceral pleural and lymphovascular invasion, and sublobar resection), and tested the hypothesis that the addition of several new molecular markers of poor long-term outcome (vascular endothelial growth factor C; microRNA precursors 486 and 30d) would enhance prediction.

METHODS

We performed a retrospective cohort study of patients with completely resected, node-negative non-small cell lung cancer from 2011 to 2014 (follow-up through 2016) using the Lung Cancer Biospecimen Resource Network. Cox regression was used to estimate the 2-year risk of recurrence. Our primary measure of model performance was the optimism-corrected C statistic.

RESULTS

Among 173 patients (mean tumor size, 3.6 cm; 12% sublobar resection, 32% poorly differentiated, 16% lymphovascular invasion, 26% visceral pleural invasion), the 2-year recurrence rate was 23% (95% confidence interval, 17% to 31%). A prediction model using five known risk factors for recurrence performed only slightly better than chance in predicting recurrence (optimism-corrected C statistic, 0.54; 95% confidence interval, 0.51 to 0.68). The addition of biomarkers did not improve the model's ability to predict recurrence (corrected C statistic, 0.55; 95% confidence interval, 0.52 to 0.71).

CONCLUSIONS

We were unable to predict lung cancer recurrence using a risk-prediction model based on five well-known clinical risk factors and several biomarkers. Further research should consider novel predictors of recurrence to stratify patients with completely resected early-stage non-small cell lung cancer according to their risk of recurrence.

Is MPP a good prognostic factor in stage III lung adenocarcinoma with EGFR exon 19 mutation?

Epidermal growth factor receptor (EGFR) is a transmembrane glycoprotein encoded by a gene located in the short arm of chromosome 7. This study aimed to investigate the clinicopathologic characteristics of classic EGFR exon mutation in Chinese patients with TMN stage III lung adenocarcinoma who received radical surgery. A total of 1,801 lung adenocarcinomas were analyzed for mutations in EGFR; 35% exhibited mutation of classic EGFR exons. Clinical and pathologic characteristics of patients with EGFR exon 19 mutation were compared with those who harbored EGFR exon 21 mutation. Patients with EGFR exon 19 mutation had a higher overall survival (OS, p=0.023) than those harboring EGFR exon 21 mutation. Our results demonstrated that patients with a micropapillary pattern (MPP) pathologic type in EGFR exon 19 mutation had a higher OS (p=0.022), and patients with exon 19 mutation were more sensitive to EGFR–tyrosine kinase inhibitors (p=0.032). The results of the current study can be used in decision-making regarding the treatment of patients with classic EGFR exon mutations.

A nomogram to predict the survival of stage IIIA-N2 non-small cell lung cancer after surgery

OBJECTIVE

Postoperative survival of patients with stage IIIA-N2 non-small cell lung cancer (NSCLC) is highly heterogeneous. Here, we aimed to identify variables associated with postoperative survival and develop a tool for survival prediction.

METHODS

A retrospective review was performed in the Surveillance, Epidemiology, and End Results database from January 2004 to December 2009. Significant variables were selected by use of the backward stepwise method. The nomogram was constructed with multivariable Cox regression. The model's performance was evaluated by concordance index and calibration curve. The model was validated via an independent cohort from the Jiangsu Cancer Hospital Lung Cancer Center.

RESULTS

A total of 1809 patients with stage IIIA-N2 NSCLC who underwent surgery were included in the training cohort. Age, sex, grade, histology, tumor size, visceral pleural invasion, positive lymph nodes, lymph nodes examined, and surgery type (lobectomy vs pneumonectomy) were identified as significant prognostic variables using backward stepwise method. A nomogram was developed from the training cohort and validated using an independent Chinese cohort. The concordance index of the model was 0.673 (95% confidence interval, 0.654-0.692) in training cohort and 0.664 in validation cohort (95% confidence interval, 0.614-0.714). The calibration plot showed optimal consistency between nomogram predicted survival and observed survival. Survival analyses demonstrated significant differences between different subgroups stratified by prognostic scores.

CONCLUSIONS

This nomogram provided the individual survival prediction for patients with stage IIIA-N2 NSCLC after surgery, which might benefit survival counseling for patients and clinicians, clinical trial design and follow-up, as well as postoperative strategy-making.

A propensity score matching analysis of survival following segmentectomy or wedge resection in early-stage lung invasive adenocarcinoma or squamous cell carcinoma

Purpose: To compare the survival outcomes following segmentectomy or wedge resection in early-stage lung cancer.

Methods: A total of 5880 patients with invasive lung adenocarcinoma or squamous cell carcinoma from the Surveillance, Epidemiology, and End Results (SEER) database were included in this study, of which 1156 received segmentectomy. Baseline characteristics were balanced using propensity score methods. Cox regression analysis was used to compare overall survival (OS) and lung cancer-specific survival (LCSS) following segmentectomy or wedge resection after matching patients based on propensity scores.

Results: Overall, patients undergoing segmentectomy and wedge resection had no significant different OS and LCSS both in the invasive adenocarcinoma group and the squamous cell carcinoma group. Segmentectomy was associated with improved OS (hazard ratio = 0.626, 95% confidence interval: 0.457-0.858, P = 0.004) and LCSS (hazard ratio = 0.643, 95% CI: 0.440-0.939, P = 0.022) in invasive adenocarcinoma patients ≤ 65 years old. In patients with ≤ 2 cm invasive adenocarcinoma, segmentectomy was associated with significantly better OS (hazard ratio = 0.811, 95% confidence interval: 0.666-0.988, P = 0.038).

Conclusion: Survival following segmentectomy or wedge resection was generally equivalent in lung invasive adenocarcinoma and squamous cell carcinoma. However, invasive adenocarcinoma patients who were ≤ 65 years or had tumors ≤ 2 cm in size may have improved survival outcomes after segmentectomy.

Long-term outcomes after near-infrared sentinel lymph node mapping in non-small cell lung cancer

OBJECTIVE

To report the first analysis of long-term outcomes using near-infrared (NIR) image-guided sentinel lymph node (SLN) mapping in non-small cell lung cancer (NSCLC).

METHODS

Retrospective analysis of patients with NSCLC enrolled in 2 prospective phase 1 NIR-guided SLN mapping trials, including an indocyanine green (ICG) dose-escalation trial, was performed. All patients underwent NIR imaging for SLN identification followed by multistation mediastinal lymph node sampling (MLNS) and pathologic assessment. Disease-free (DFS) and overall survival (OS) were compared between patients with NIR⁺ SLN (SLN group) and those without (non-SLN group).

RESULTS

SLN detection, recurrence, DFS, and OS were assessed in 42 patients with NSCLC who underwent intraoperative peritumoral ICG injection, NIR imaging, and MLNS. NIR⁺ SLNs were identified in 23 patients (SLN group), whereas SLNs were not identified in 19 patients enrolled before ICG dose and camera optimization (non-SLN group). Median follow-up was 44.5 months. Pathology from NIR⁺ SLNs was concordant with overall nodal status in all 23 patients. Sixteen patients with SLN were deemed pN0 and no recurrences were, whereas 4 of 15 pN0 non-SLN patients developed nodal or distant recurrent disease. Comparing SLN versus non-SLN pN0 patients, the probability of 5-year OS is 100% versus 70.0% (P = .062) and 5-year DFS is statistically significantly improved at 100% versus 66.1% (P = .036), respectively. Among the 11 pN+ patients, 7 were in the SLN group, with >40% showing metastases in the SLN alone.

CONCLUSIONS

Patients with pN0 SLNs showed favorable disease-free and overall survival. This preliminary review of NIR SLN mapping in NSCLC suggests that pN0 SLNs may better represent true N0 status. A larger clinical trial is planned to validate these findings.

Diagnosis, clinicopathological characteristics and prognosis of pulmonary mucinous adenocarcinoma

Primary pulmonary mucinous adenocarcinoma (PPMA) is an uncommon subtype of lung adenocarcinoma. The present study attempted to clarify the diagnosis, clinicopathological characteristics, and pathologic significance of epithelial growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene (KRAS) mutations and the prognosis of PPMA. A total of 29 patients with PPMA from among 1,469 surgically resected patients with lung adenocarcinoma were enrolled. All of the tumours expressed CK7 and 5 cases exhibited co-expression with CK20. A total of 8 cases expressed EGFR, 14 cases expressed P53 and 2 cases expressed CEA. The majority of mucinous adenocarcinomas expressed thyroid transcription factor 1, Napsin A, Villin and Cam5.2 proteins. KRAS mutations were observed in 62% of patients and were more prevalent in the lower lung lobe and in patients with invasive mucinous adenocarcinoma. A total of 2 cases exhibited an EGFR mutation, and the co-mutation of KRAS and EGFR was only detected in 1 case. The relapse-free and overall survival rates at 5 years were 70.4, and 81.5%, respectively. The results may assist to identify a molecular target and supply important information for a therapeutic strategy for patients with PPMA.

A Model to Predict the Use of Surgical Resection for Advanced-Stage Non-Small Cell Lung Cancer Patients

BACKGROUND

For advanced-stage non-small cell lung cancer, chemotherapy and chemoradiotherapy are the primary treatments. Although surgical intervention in these patients is associated with improved survival, the effect of selection bias is poorly defined. Our objective was to characterize selection bias and identify potential surgical candidates by constructing a Surgical Selection Score (SSS).

METHODS

Patients with clinical stage IIIA, IIIB, or IV non-small cell lung cancer were identified in the National Cancer Data Base from 1998 to 2012. Logistic regression was used to develop the SSS based on clinical characteristics. Estimated area under the receiver operating characteristic curve was used to assess discrimination performance of the SSS. Kaplan-Meier analysis was used to compare patients with similar SSSs.

RESULTS

We identified 300,572 patients with stage IIIA, IIIB, or IV non-small cell lung cancer without missing data; 6% (18,701) underwent surgical intervention. The surgical cohort was 57% stage IIIA (n = 10,650), 19% stage IIIB (n = 3,483), and 24% stage IV (n = 4,568). The areas under the receiver operating characteristic curve from the best-fit logistic regression model in the training and validation sets were not significantly different, at 0.83 (95% confidence interval, 0.82 to 0.83) and 0.83 (95% confidence interval, 0.82 to 0.83). The range of SSS is 43 to 1,141. As expected, SSS was a good predictor of survival. Within each quartile of SSS, patients in the surgical group had significantly longer survival than nonsurgical patients (p < 0.001).

CONCLUSIONS

A prediction model for selection of patients for surgical intervention was created. Once validated and prospectively tested, this model may be used to identify patients who may benefit from surgical intervention.

Molecular characteristics of multifocal invasive mucinous adenocarcinoma of the lung: Report of a rare case

Invasive mucinous adenocarcinoma (IMA) is an uncommon entity in the lung, with a poor prognosis. Multifocal IMA of the lung is even more unusual, and there is little experience with effective treatments. Herein, we present a case of multifocal IMA diagnosed in a 36 year‐old man by video‐assisted thoracoscopic surgery. A right middle lobe and a nodule in the right upper lobe were resected, as were mediastinal lymph nodes, leaving behind an autonomous right lower lobe nodule. To explore the feasibility of molecular treatment, next‐generation sequencing of genetic mutations was performed after four cycles of chemotherapy (pemetrexed + cisplatin). Ultimately, a KIAA1468‐RET fusion gene was detected at a disproportionate level (~67.3%), indicating that targeted therapy may be efficacious in treating this disease.

Development and validation of two prognostic nomograms for predicting survival in patients with non-small cell and small cell lung cancer

Purpose

This study aimed to construct two prognostic nomograms to predict survival in patients with non-small-cell lung cancer (NSCLC) and small-cell lung cancer (SCLC) using a novel set of clinical parameters.

Patients and Methods

Two nomograms were developed, using a retrospective analysis of 5384 NSCLC and 647 SCLC patients seen during a 10-year period at Xiang Ya Affiliated Cancer Hospital (Changsha, China). The patients were randomly divided into training and validation cohorts. Univariate and multivariate analyses were used to identify the prognostic factors needed to establish nomograms for the training cohort. The model was internally validated via bootstrap resampling and externally certified using the validation cohort. Predictive accuracy and discriminatory capability were estimated using concordance index (C-index), calibration curves, and risk group stratification.

Results

The largest contributor to overall survival (OS) prognosis in the NSCLC nomogram was the therapeutic regimen and diagnostic method parameters, and in the SCLC nomogram was the therapeutic regimen and health insurance plan parameters. Calibration curves for the nomogram prediction and the actual observation were in optimal agreement for the 3-year OS and acceptable agreement for the 5-year OS in both training datasets. The C-index was higher for the NSCLC cohort nomogram than for the TNM staging system (0.67 vs. 0.64, P = 0.01) and higher for the SCLC nomogram than for the clinical staging system (limited vs. extensive) (0.60 vs. 0.53, P = 0.12).

Conclusion

Treatment regimen parameter made the largest contribution to OS prognosis in both nomograms, and these nomograms might provide clinicians and patients a simple tool that improves their ability to accurately estimate survival based on individual patient parameters rather than using an averaged predefined treatment regimen.

Nomograms for predicting recurrence and survival of invasive pathological stage IA non-small cell lung cancer treated by video assisted thoracoscopic surgery lobectomy

BACKGROUND

A considerable portion of pathological stage (p-stage) IA non-small cell lung cancer (NSCLC) patients suffered from death and recurrence after video assisted thoracoscopic surgery (VATS) lobectomy. The purpose of our study was to develop nomograms to predict which subgroup patients were more likely to suffer from recurrence or death.

METHODS

Data of invasive p-stage IA NSCLC patients who underwent VATS lobectomy at Peking University People's Hospital from September 2006 to April 2014 were analyzed. Multivariate Cox proportional hazards regression was used to develop nomograms. The performance of the nomograms was evaluated by Harrell's concordance index (C-index), calibration plots and risk group stratification.

RESULTS

A total of 422 patients with NSCLC of invasive p-stage IA were included in the study. The median follow-up time was 40 months. Age [hazards ratio (HR) =1.067, 95% confidential interval (CI): 1.006-1.131], lymphovascular invasion (LVI) (HR=4.062, 95% CI: 1.278-12.912) and differentiation (HR =5.747, 95% CI: 2.151-15.353) were independent prognostic factors to predict overall survival (OS). Tumor diameter (HR =3.299, 95% CI: 1.814-6.001), LVI (HR =3.260, 95% CI: 1.221-8.708) and differentiation (HR =3.607, 95% CI: 1.776-7.327) were independent predictors of recurrence free survival (RFS). The nomogram for predicting OS demonstrated stronger discriminatory power than the 7th and 8th T stage systems (C-index: 0.894 for the nomogram, 0.700 for the 7th T stage and 0.742 for the 8th T stage). Likewise, the C-index of the nomogram for predicting RFS was higher than that of the 7th and 8th T stage systems (0.838 for the nomogram, 0.670 for the 7th T stage and 0.723 for the 8th T stage).

CONCLUSIONS

We developed nomograms that could predict individual accurate prognosis for invasive p-stage IA NSCLC patients after VATS lobectomy. Risk stratification by the nomograms might guide further adjuvant chemotherapy and follow-up.

Inaccuracy of lung adenocarcinoma subtyping using preoperative biopsy specimens

BACKGROUND

The prognostic significance of the new classification of lung adenocarcinoma proposed in the 2015 World Health Organization guideline has been validated. This study aimed to compare the preoperative classification of the adenocarcinoma subtype based on computed tomography-guided 18-gauge core needle biopsy (CTNB) or radial probe endobronchial ultrasound (R-EBUS) specimens, with the postoperative classification based on the resected specimens.

METHODS

We retrospectively analyzed a consecutive series of 128 patients (60 CTNB and 68 R-EBUS) who underwent surgery for preoperatively confirmed lung adenocarcinoma between 2010 and 2014. Comprehensive histological subtyping was performed according to the 2015 World Health Organization classification system. Diagnostic concordance of subtypes between small biopsy and resection specimens was assessed.

RESULTS

Concordant subtyping of adenocarcinomas between the predominant pattern on resections and biopsy sections was observed in 58.6% of cases (75 of 128; 95% confidence interval [CI], 49.9%-66.8%). Preoperative subtyping was accurate in only 30% of samples (3 of 10) with a predominance of solid patterns. None of the 5 micropapillary predominant cases was detected by CTNB or R-EBUS. For the concordance of the presence or absence of micropapillary/solid component, the sensitivity was as low as 16.5% (95% CI, 9.1%-26.5%). The detection rate by CTNB/R-EBUS increased with the increase in the percentage of micropapillary/solid component; however, even in the ≥40% micropapillary/solid group, only 24% of cases were detected by CTNB/R-EBUS.

CONCLUSIONS

The accuracy of the estimation of adenocarcinoma histological subtype based on preoperative biopsy sections was unsatisfactory.

Optimal delivery of follow-up care following pulmonary lobectomy for lung cancer

Introduction

The rationale for oncologic surveillance following pulmonary lobectomy is to detect recurrent disease or a second primary lung cancer early enough so that an intervention can increase survival and/or improve quality of life. Therefore, we reviewed literature for international guidelines and reorganized these useful factors associated with non-small-cell lung cancer (NSCLC) recurrence as remedies in postoperative follow-up.

Method

The population of interest for this review was patients who had been treated with complete resection for primary NSCLC and were in follow-up.

Result

Guidelines on follow-up care for NSCLC vary internationally. Because of the production of progressive medical modalities, the current follow-up care should be corrected.

Conclusion

The specific follow-up schedule for computed tomography imaging may be more or less frequent, depending upon risk factors for recurrence. Many different predictors of postoperative recurrence may help to optimize the patient selection for specified surveillance guidelines and personalized adjuvant therapies to prevent possibly occult micrometastases and to get a better outcome.