The Role of Surgery in High-Grade Neuroendocrine Cancer: Indications for Clinical Practice

Implementing machine learning to predict survival outcomes in patients with resected pulmonary large cell neuroendocrine carcinoma

BACKGROUND

The post-surgical prognosis for Pulmonary Large Cell Neuroendocrine Carcinoma (PLCNEC) patients remains largely unexplored. Developing a precise prognostic model is vital to assist clinicians in patient counseling and creating effective treatment strategies.

RESEARCH DESIGN AND METHODS

This retrospective study utilized the Surveillance, Epidemiology, and End Results database from 2000 to 2018 to identify key prognostic features for Overall Survival (OS) in PLCNEC using Boruta analysis. Predictive models employing XGBoost, Random Forest, Decision Trees, Elastic Net, and Support Vector Machine were constructed and evaluated based on Area Under the Receiver Operating Characteristic Curve (AUC), calibration plots, Brier scores, and Decision Curve Analysis (DCA).

RESULTS

Analysis of 604 patients revealed eight significant predictors of OS. The Random Forest model outperformed others, with AUC values of 0.765 and 0.756 for 3 and 5-year survival predictions in the training set, and 0.739 and 0.706 in the validation set, respectively. Its superior validation cohort performance was confirmed by its AUC, calibration, and DCA metrics.

CONCLUSIONS

This study introduces a novel machine learning-based prognostic model with a supportive web-based platform, offering valuable tools for healthcare professionals. These advancements facilitate more personalized clinical decision-making for PLCNEC patients following primary tumor resection.

Prognostic factors and nomogram for pulmonary resected high-grade neuroendocrine carcinomas: a 20-year single institutional real-world experience

BACKGROUND

Pulmonary high-grade neuroendocrine carcinomas(pHGNEC) encompassing small cell lung cancer (SCLC) and large cell neuroendocrine carcinoma (LCNEC) are clinically aggressive tumors with poor prognosis. The role of surgery and prognostic factors guiding management remain unclear. We aimed to analyze prognosis following resection and identify predictive variables.

METHODS

This retrospective study analyzed 259 patients undergoing pHGNEC resection from 2001-2023. Overall survival (OS) and disease-free survival (DFS) were evaluated using Kaplan-Meier curves. Prognostic factors were assessed with Cox regression and visualized using nomogram tools.

RESULTS

Minimally invasive surgery was associated with better OS (p = 0.001) and DFS (p = 0.001). Higher T stage predicted worse OS (T2 p = 0.044, T4 p = 0.007) and DFS (T2 p = 0.020, T4 p = 0.004). Advanced TNM stage III (OS p = 0.018; DFS p = 0.015) and IV (OS p < 0.001; DFS p < 0.001) also correlated with poorer prognosis. In the SCLC subgroup, elevated preoperative CEA independently predicted worse OS (p = 0.012) and DFS (p = 0.004). T4 disease (OS p < 0.001; DFS p = 0.002) and advanced TNM staging (stage III OS p = 0.043; DFS p = 0.045; stage IV OS p < 0.001, DFS p < 0.001) were associated with worse outcomes. In LCNEC patients, VATS resection improved OS (p = 0.048) and DFS (p = 0.027) despite conversion. Prior malignancy predicted worse OS (p < 0.001). Advanced TNM disease (stage III OS p = 0.047; stage IV OS p = 0.003, DFS p = 0.005) were also negative prognostic factors. The prognostic nomogram incorporating above variables effectively stratified risk. Calibration plots revealed good correlation between predicted and actual survival.

CONCLUSIONS

We identified minimally invasive surgery, early TNM stage, younger age, and normal preoperative CEA as positive prognostic factors following pHGNEC resection. Our study provides an applicable prognostic nomogram to facilitate personalized pHGNEC management.

Development and validation of nomograms to predict survival of neuroendocrine carcinoma in genitourinary system: A population-based retrospective study

Neuroendocrine carcinoma (NEC) is a rare yet potentially perilous neoplasm. The objective of this study was to develop prognostic models for the survival of NEC patients in the genitourinary system and subsequently validate these models. A total of 7125 neuroendocrine neoplasm (NEN) patients were extracted. Comparison of survival in patients with different types of NEN before and after propensity score-matching (PSM). A total of 3057 patients with NEC, whose information was complete, were extracted. The NEC influencing factors were chosen through the utilization of the least absolute shrinkage and selection operator regression model (LASSO) and the Fine & Gary model (FGM). Furthermore, nomograms were built. To validate the accuracy of the prediction, the efficiency was verified using bootstrap self-sampling techniques and receiver operating characteristic curves. LASSO and FGM were utilized to construct three models. Confirmation of validation was achieved by conducting analyses of the area under the curve and decision curve. Moreover, the FGS (DSS analysis using FGM) model produced higher net benefits. To maximize the advantages for patients, the FGS model disregarded the influence of additional occurrences. Patients are expected to experience advantages in terms of treatment options and survival assessment through the utilization of these models.

Survival of small-cell lung cancer patients after surgery: A single-center retrospective cohort study

This study summarized and analyzed the clinical characteristics and prognosis of small-cell lung cancer (SCLC) patients after surgical treatment. The clinical data of 130 patients (99 males and 31 females) with SCLC treated by surgery and confirmed by postoperative pathological examination at Peking Union Medical College Hospital from April 2004 to April 2019 were retrospectively analyzed. Clinical characteristics, surgery, pathological stage, and perioperative treatment were summarized. Kaplan-Meier survival curve and Cox regression analysis were performed. Pathological examination revealed that 36 (27.69%) patients had stage I SCLC, 22 (16.92%) patients had stage II SCLC, 65 (50.00%) patients had stage III SCLC, and 7 (5.39%) patients had stage IV SCLC. The overall median survival time was 50 months (95% confidence interval, 10.8-89.2 months). The median survival time of stage I, II, III and IV SCLC patients was 148, 42, 32, and 10 months, respectively. In patients who underwent surgical treatment, postoperative adjuvant therapy and tumor stage were independent prognostic factors for survival (p < 0.05).Lobectomy and lymph nodes resection combined with adjuvant therapy were cautiously recommended for stage I-IIIa SCLC patients.

[Development and Validation of A Prognostic Nomogram to Guide Decision-making in Lung Large Cell Neuroendocrine Carcinoma]

BACKGROUND

Lung large cell neuroendocrine carcinoma (LCNEC) is a rare and highly malignant lung tumor with a poor prognosis. Currently, most research on LCNEC is based on retrospective studies and lacks validation in the real world. The study aims to identify independent risk factors and establish and validate a predictive model for the prognosis of LCNEC.

METHODS

Patient data were extracted from Surveillance, Epidemiology, and End Results (SEER) and our department's hospitalization records from 2010 to 2015 and 2016 to 2020, respectively. Kaplan-Meier analysis was used to evaluate overall survival (OS). OS is defined as the time from diagnosis to death or last follow-up for a patient. Univariate and multivariate Cox regression analyses were performed to identify significant prognostic factors and construct a Nomogram for predicting the prognosis of LCNEC.

RESULTS

In total, 1892 LCNEC patients were included and divided into a training cohort (n=1288) and two validation cohorts (n=552, n=52). Univariate Cox regression analysis showed that age, gender, primary tumor site, laterality, T stage, N stage, M stage, surgery, and radiotherapy were factors that could affect the prognosis of LCNEC patients (P<0.05). Multivariate Cox analysis indicated that age, gender, primary tumor site, T stage, N stage, M stage, surgery, and radiotherapy were independent risk factors for the prognosis of LCNEC patients (P<0.05). Calibration curves and the concordance index (internal: 0.744±0.015; external: 0.763±0.020, 0.832±0.055) demonstrated good predictive performance of the model.

CONCLUSIONS

Patients aged ≥65 years, male, with advanced tumor-node-metastasis (TNM) staging, and who have not undergone surgery or radiotherapy have a poor prognosis. Nomogram can provide a certain reference for personalized clinical decision-making for patients.

The survival benefit from surgery on patients with large-cell neuroendocrine carcinoma in the lung: a propensity-score matching study

PURPOSE

This study aimed to investigate the prognostic significance of surgery in large-cell neuroendocrine carcinoma (LCNC) patients.

METHODS

A total of 453 patients from the Surveillance, Epidemiology, and End Results database diagnosed with stage T1-4N0-2M0 LCNC from 2010 to 2015 were analyzed. The propensity-score matching analysis with a ratio of 1:1 was used to minimize the bias effect of other clinical characteristics, and 77 pairs of patients' data were performed for subsequent statistical analysis. The Cox proportional hazards model, Kaplan-Meier analysis, and Log-rank test were used in the present study. The primary observational endpoint was cancer-specific survival (CSS).

RESULTS

The 1-year, 3-year, and 5-year CSS rates were 60.0%, 45.0%, and 42.0% in those 453 LCNC patients. Compared with patients who underwent surgical resection, patients without surgery had a lower 5-year CSS rate (18.0% vs. 52.0%, P < 0.001). After analyses of multivariable Cox regression, chemotherapy, T stage, N stage, and surgery were identified as independent prognostic indicators (all P < 0.05). In the cohort of old patients, the median survival time was longer in cases after surgery than those without surgery (13.0 months vs. NA, P < 0.001). Besides, in patients with different clinical characteristics, the receiving surgery was a protective prognostic factor (all hazard ratio < 1, all P < 0.05). In addition, for the cohort with stage T1-2N0-2M0, patients after the operation had more improved outcomes than patients without surgery (P < 0.001).

CONCLUSIONS

We proposed that the surgery could improve the survival outcomes of LCNC patients with stage T1-4N0-2M0. Moreover, old patients could benefit from surgery.

Neuroendocrine Neoplasms: Epidemiology, Diagnosis, and Management

Neuroendocrine tumors have variety of biological and clinical characteristics. The classification of neuroendocrine neoplasm has evolved, and the newest 2019 World Health Organization classification outlines a well-differentiated high-grade G3 subtype, recognizing its differences from the poorly differentiated neuroendocrine carcinoma. ⁶⁸Ga-DOTAT PET has largely replaced somatostatin scintigraphy as the diagnostic workup choice for NENs. NETest, a multi-analyte liquid biopsy, is a promising recent development in the biochemical diagnosis. Management includes wait and watch approach, surgical resection, somatostatin analogs, ¹⁷⁷Lu DOTATATE therapy, chemotherapy, radiotherapy or immunotherapy combinations. Further clinical trials are necessary for determining the appropriate sequencing.

Surgical Principles in the Management of Lung Neuroendocrine Tumors: Open Questions and Controversial Technical Issues

OPINION STATEMENT

Primary neuroendocrine tumors (NETs) of the lung represent a heterogeneous group of malignancies arising from the endocrine cells, involving different entities, from well differentiated to highly undifferentiated neoplasms. Because of the predominance of poorly differentiated tumors, advanced disease is observed at diagnosis in more than one third of patients making chemo- or chemoradiotherapy the only possible treatment. Complete surgical resection, as defined as anatomical resection plus systematic lymphadenectomy, becomes a reliable curative option only for that little percentage of patients presenting with stage I (N0) high-grade NETs. On the other hand, complete surgical resection is considered the mainstay treatment for localized low- and intermediate-grade NETs. Therefore, in the era of the mini-invasive surgery, their indolent behavior has suggested that parenchyma-sparing resections could be as adequate as the anatomical ones in terms of oncological outcomes, leading to discuss about the correct extent of resection and about the role of lymphadenectomy when dealing with highly differentiated NETs.