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

Clinical significance of postoperative folate receptor-positive circulating tumor cells (FR + CTCs) for long-term prognosis in patients with invasive adenocarcinoma (IAC) of the lung

BACKGROUND

The aim of the study was to evaluate the prognostic value of postoperative folate receptor-positive circulating tumor cell (FR + CTC) detection in patients with stage I-III invasive adenocarcinoma (IAC) treated with surgery.

METHODS

Patients with lung adenocarcinoma (LUAD) who underwent surgical resection in Peking University Cancer Hospital and received postoperative FR + CTC analysis from July 2016 to January 2021 were retrospectively collected. Comparisons between or among groups were made using the Kruskal-Wallis or Mann-Whitney U tests. Survival curves were estimated using the Kaplan-Meier method and compared using the log-rank test. Cox proportional hazard regression analyses were performed to explore the factors predicting recurrence and survival.

RESULTS

There were significant differences between the high and low groups in terms of age (p = 0.002), postoperative CA199 (p = 0.038), and postoperative SCC (p = 0.024). There were no significant differences in the other indicators (all p>0.05). N stage 1, N stage 2, and neoadjuvant therapy (NAT) were independent risk factors for disease recurrence and death; pleural invasion (PI), and nerve invasion were independent risk factors for death. The Kaplan-Meier curve showed a notable trend for a worse disease-free survival (DFS) or overall survival (OS) for patients with high levels of FR + CTCs in our study, but none of these were statistically significant.

CONCLUSION

The detection of FR + CTCs postoperatively was an independent predictor of recurrence in patients treated for stage I-III IAC. Standardized detection methods and optimal time points for assessment should be established in future studies.

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.

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.

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.

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.

Performance of a Nomogram Based on the Integration of Inflammation Markers with Tumor Staging in Prognosis Prediction of Stage III Colorectal Cancer

Introduction

The aim of the present study was to evaluate a nomogram model for predicting the 5-year overall survival (OS) in lymph node-metastatic colorectal cancer (CRC) patients by combining inflammation markers with some traditional prognostic factors.

Methods

A total of 399 patients with stage III (pT_XN_1-3M₀) CRC operated from January 2007 to December 2012 were enrolled in this retrospective study. All patients underwent D₂ lymphadenectomy in the hospital. A prognostic nomogram based on the integration of traditional prognostic factors and NLR (neutrophil-to-lymphocyte ratio) and PLR (platelet-to-lymphocyte ratio) was established and compared with the nomogram based on the traditional prognostic factors alone. ROC curves were further applied to verify the predictive accuracy of the established model.

Results

Both NLR (P=0.00) and PLR (P=0.01) predicted the 5-year OS. In multivariate analysis, age, T3 category, T4 category, N2 category, N3 category, Pgp (P-glycoprotein), NLR and PLR are proven to be independent (all P≤0.05). The established nomogram showed better predictive power than that of traditional profile (c-index: 0.66 versus 0.63) in both training and validation cohorts. External assessment by ROC curve analysis demonstrated that the established model had a good prediction accuracy of 5-year OS in stage III CRC patients, with area under curve values of 0.657 and 0.629 in training and validating sets, respectively.

Conclusion

A nomogram based on the integration of traditional prognostic factors and inflammatory markers (NLR and PLR) could provide more precise long-term prognosis information for lymph node-metastatic CRC patients than the model based on traditional profile alone. This model might be useful for clinical application in personalized evaluation.

Development and validation of a nomogram for predicting cancer-specific survival of surgical resected stage I-II adenosquamous carcinoma of the lung

OBJECTIVES

Primary lung adenosquamous carcinoma (ASC) is a rare cancer subtype and has a poor prognosis. The prognostic factors for resected early-stage ASC remain unclear. We aimed to develop a nomogram to predict lung cancer-specific survival (LCSS) of patients undergoing surgical resection for stage I-II ASC.

METHODS

Data of patients undergoing resection for stage I-II ASC and diagnosed between 2004-2015 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. All the included patients were randomized at a 7:3 ratio into a training and a validation cohort. We selected and integrated significant prognostic factors based on competing for risk regression to build a nomogram. The performance of the nomogram was evaluated using Harrell's concordance index (C-index) and calibration plots.

RESULTS

A total of 988 patients (530 men and 458 women) undergoing surgical resection for stage I-II ASC were identified and randomized into a training (692, 70%) cohort and a validation cohort (296, 30%). The baseline characteristics were similar in the training and validation cohorts. Age, T stage, N stage, and the number of examined lymph nodes were independent prognostic factors for LCSS and were used in the nomogram. The calibration plots showed that the 3- and 5-year LCSS probabilities were consistent between the nomogram prediction and the actual observation. The C-index of the nomogram was 0.671 (95%CI: 0.618-0.724) and 0.635 (95%CI: 0.557-0.713) in the training cohort and validation cohort, respectively. We developed a risk classification system based on the nomogram to stratify patients into high- and low-risk of cancer-specific death groups. Patients with a similar risk shared similar prognostic prediction regardless of the stage category and patients with the same risk shared similar prognoses despite the different stage category.

CONCLUSIONS

We developed a competing risk nomogram to reliably predict cancer-specific survival of patients undergoing surgical resection for stage I-II ASC. The nomogram might be a useful tool to identify patients undergoing surgical resection for ASC who could be suitable candidates for adjuvant chemotherapy.

Patterns and risks of postoperative recurrence in completely resected EGFR-mutant non-small cell lung cancer: prognostic significance of routine immunohistochemical markers

Background

Recent studies indicate that EGFR-mutant non-small cell lung cancer (NSCLC) is a heterogeneous disease with varying prognosis. In order to design an optimized surveillance strategy and identify potential candidates for adjuvant therapy, the patterns and risks of postoperative recurrence in completely resected EGFR-mutant NSCLC should be investigated, which are currently largely unknown.

Methods

Consecutive patients with curatively resected EGFR-positive NSCLC receiving standard adjuvant chemotherapy without EGFR tyrosine kinase inhibitors (TKI), with or without adjuvant radiotherapy, from January 2007 to December 2017 in our cancer center, were retrospectively reviewed. Prognostic significance of ten routine immunohistochemical (IHC) markers were examined.

Results

After a median follow-up of 32 (range, 5-122) months, disease recurrence occurred in 197 (37.1%) of the 531 enrolled patients. The frequencies of thoracic recurrence, brain recurrence, bone recurrence, abdominal recurrence and neck recurrence, were 69.0%, 20.8%, 20.8%, 7.1% and 6.6%, respectively. Using the Cox regression model, tumor size, Ki67, CK20, and N stage were identified as independent predictors of overall recurrence. A nomogram predicting the 1-, 2-, and 3-year cumulative rate of overall recurrence was then developed and internally validated, with a bias-corrected C-index of 0.723 (95% CI, 0.675 to 0.771) and a small extent of "over-fitting" (0.8%). Risk factors of site-specific recurrence were also discovered. Additionally, using competing risk analyses, N stage, lymphovascular invasion (LVI) and CK5/6 were found as independent predictors of loco-regional recurrence. Among patients with N2-positive disease (n=91), adjuvant radiotherapy tended to prolong disease free survival (DFS) (P=0.067), but not overall survival (OS) (P=0.271).

Conclusions

This study provides the proof of concept of using routine IHC markers, along with common clinical-pathological parameters, in predicting postoperative recurrence among completely resected EGFR-mutant NSCLC. Adjuvant radiotherapy may improve DFS, but hard to prolong OS in N2-positive EGFR-mutant NSCLC without further biomarker-guided patients' selection.

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.

Stereotactic body radiotherapy with adjuvant systemic therapy for early-stage non-small cell lung carcinoma: A multi-institutional analysis

PURPOSE

Although adjuvant systemic therapy (ST) is often recommended for the treatment of patients with high-risk, early-stage non-small cell lung carcinoma (NSCLC) after surgery, there is little evidence supporting the use of ST with stereotactic body radiotherapy (SBRT).

METHODS

We conducted a retrospective cohort study using a multi-institutional database to identify consecutive patients with T1-3N0M0 NSCLC treated with definitive SBRT from 2006-2015. Treatment groups were defined as those who received SBRT + ST or SBRT alone. Regional-distant failure (RDF) was analyzed with Fine and Gray competing risks regression. Progression-free (PFS) and overall survival (OS) were analyzed with the Kaplan-Meier method and Cox regression. Additional comparisons were made after 2:1 nearest-neighbor propensity-score matching on clinical risk factors.

RESULTS

We identified 54 patients who received SBRT + ST. The most common ST regimen was a platinum doublet (n = 38; 70.4%). Compared with patients receiving SBRT (n = 1269), SBRT + ST patients were younger (median age: 70 v 77 years, p < 0.001), had larger tumors (>3 cm: 38.9% v 21.6%, p = 0.02) and higher T-stage (T2-3: 42.6% v 22.5%, p = 0.002). Compared with SBRT patients, SBRT + ST patients had lower 2-year RDF (3.1% v 16.9%, p = 0.02). On multivariable analysis, SBRT + ST was associated with reduced RDF (HR: 0.15, 95%CI: 0.04-0.62), with a trend toward improved PFS (HR: 0.70, 95%CI: 0.48-1.03), but not OS (HR: 0.74, 95%CI: 0.49-1.11). After propensity-score matching, the SBRT + ST cohort demonstrated improved RDF (HR: 0.17, 95%CI: 0.04-0.76) and PFS (HR: 0.59, 95%CI: 0.38-0.93).

CONCLUSION

In this multi-institutional analysis, adjuvant ST was independently associated with reduced RDF in early-stage NSCLC patients treated with SBRT.