Prognostic significance of laterality in lung neuroendocrine tumors

Predictive Modeling of Long-Term Prognosis After Resection in Typical Pulmonary Carcinoid: A Machine Learning Perspective

Typical Pulmonary Carcinoid (TPC) is defined by its slow growth, frequently necessitating surgical intervention. Despite this, the long-term outcomes following tumor resection are not well understood. This study examined the factors impacting Overall Survival (OS) in patients with TPC, leveraging data from the Surveillance, Epidemiology, and End Results database spanning from 2000 to 2018. We employed Lasso-Cox analysis to identify prognostic features and developed various models using Random Forest, XGBoost, and Cox regression algorithms. Subsequently, we assessed model performance using metrics such as Area Under the Curve (AUC), calibration plot, Brier score, and Decision Curve Analysis (DCA). Among the 2687 patients, we identified five clinical features significantly affecting OS. Notably, the Random Forest model exhibited strong performance, achieving 5- and 7-year AUC values of 0.744/0.757 in the training set and 0.715/0.740 in the validation set, respectively, outperforming other models. Additionally, we developed a web-based platform aimed at facilitating easy access to the model. This study presents a machine learning model and a web-based support system for healthcare professionals, assisting in personalized treatment decisions for patients with TPC post-tumor resection.

Prognosis of unresected versus resected early-stage pulmonary carcinoid tumors ≤3 cm in size: A population-based study

PURPOSE

The observation-based prognosis, rather than resection, for small carcinoid tumors is still unclear. This lack of clarity has important implications for counseling elderly patients or patients for whom surgical resection poses a high risk. This study compared the outcomes of observation and surgical resection in patients with pulmonary carcinoid (PC) tumors ≤3 cm in size without metastasis.

METHODS

Data of patients with PC tumors with ≤3 cm in diameter and without lymph node and distant metastases were retrieved from Surveillance, Epidemiology, and End Results (SEER) registry. To reduce the inherent bias of retrospective studies, propensity score matching analysis was performed. Overall survival (OS) and lung carcinoid-specific survival (LCSS) were analyzed using Kaplan-Meier plots. Multivariate analysis was used to determine predictors of LCSS in different size subgroups.

RESULTS

In total, 4552 patients with early-stage PCs ≤3 cm in diameter, including 435 (9.56%) who were observed and 4117 (90.44%) treated by surgery, were recruited. Patients with surgery had significantly better OS and LCSS than those who were observed. However, patients with observation had comparable LCSS to those with surgery for PCs with tumor diameters ≤1 cm. Multivariate analysis indicated that surgical resection was an independent prognostic factor for LCSS in 1 cm < tumors ≤2 cm, and 2 cm < tumors ≤3 cm groups, but not for tumors ≤1 cm in diameter.

CONCLUSION

Surgical resection of small PCs is associated with a survival advantage over observation. However, for early PCs ≤1 cm in diameter, observation may be considered in patients with high risk for surgical resection.

Recent advances and future challenges in the diagnosis of neuroendocrine neoplasms

Neuroendocrine neoplasms (NEN) are a heterogeneous group of malignancies with increasing incidence, whose diagnosis is usually delayed, negatively impacting on patients' prognosis. The latest advances in pathological classifications, biomarker identification and imaging techniques may provide early detection, leading to personalized treatment strategies. In this narrative review the recent developments in diagnosis of NEN are discussed including progresses in pathological classifications, biomarker and imaging. Furthermore, the challenges that lie ahead are investigated. By discussing the limitations of current approaches and addressing potential roadblocks, we hope to guide future research directions in this field. This article is proposed as a valuable resource for clinicians and researchers involved in the management of NEN. Update of pathological classifications and the availability of standardized templates in pathology and radiology represent a substantially improvement in diagnosis and communication among clinicians. Additional immunohistochemistry markers may now enrich pathological classifications, as well as miRNA profiling. New and multi-analytical circulating biomarkers, as liquid biopsy and NETest, are being proposed for diagnosis but their validation and availability should be improved. Radiological imaging strives for precise, non-invasive and less harmful technique to improve safety and quality of life in NEN patient. Nuclear medicine may benefit of somatostatin receptors' antagonists and membrane receptor analogues. Diagnosis in NEN still represents a challenge due to their complex biology and variable presentation. Further advancements are necessary to obtain early and minimally invasive diagnosis to improve patients' outcomes.

Rachel score: a nomogram model for predicting the prognosis of lung neuroendocrine tumors

BACKGROUND

Lung NET, classified in typical carcinoids (TC) and atypical carcinoids (AC), are highly heterogeneous in their biology and prognosis. The histological subtype and TNM stage are well-established prognostic factors for lung NET. In a previous work by our group, we demonstrated a significant impact of laterality on lung NET survival outcomes.

MATERIALS AND METHODS

We developed a nomogram that integrates relevant prognostic factors to predict lung NET outcomes. By adding the scores for each of the variables included in the model, it was possible to obtain a prognostic score (Rachel score). Wilcoxon non-parametric statistical test was applied among parameters and Harrell's concordance index was used to measure the models' predictive power. To test the discriminatory power and the predictive accuracy of the model, we calculated Gonen and Heller concordance index. Time-dependent ROC curves and their area under the curve (AUC) were used to evaluate the models' predictive performance.

RESULTS

By applying Rachel score, we were able to identify three prognostic groups (specifically, high, medium and low risk). These three groups were associate to well-defined ranges of points according to the obtained nomogram (I: 0-90, II: 91-130; III: > 130 points), providing a useful tool for prognostic stratification. The overall survival (OS) and progression free survival (PFS) Kaplan-Meier curves confirmed significant differences (p < 0.0001) among the three groups identified by Rachel score.

CONCLUSIONS

A prognostic nomogram was developed, incorporating variables with significant impact on lung NET survival. The nomogram showed a satisfactory and stable ability to predict OS and PFS in this population, confirming the heterogeneity beyond the histopathological diagnosis of TC vs AC.

Risk of metastasis and survival in patients undergoing different treatment strategies with T1 colonic neuroendocrine tumors

PURPOSE

The efficacy and safety of local excision (LE) for small (< 1‒2 cm) colonic neuroendocrine tumors (NETs) is controversial due to the higher metastasis risk when compared with rectal NETs. The study aimed to evaluate the metastasis risk of T1 colonic NETs and compare patients' long-term prognosis after LE or radical surgery (RS).

METHODS

The Surveillance Epidemiology and End Results database was used to identify patients with T1 colonic NETs (2004‒2015). Multivariable logistic regression was performed to assess factors associated with metastasis risk. Propensity score matching was used to balance the variables. Cancer-specific survival (CSS) and overall survival (OS) were calculated to estimate the prognosis of patients with T1N0M0 colonic NETs who underwent LE or RS.

RESULTS

Of the 610 patients with colonic NETs, 46 (7.54%) had metastasis at diagnosis. Tumor size (11-20 mm) (OR = 9.51; 95% confidence interval (CI): 4.32‒21.45; P < 0.001), right colon (OR = 15.79; 95% CI 7.20‒38.56; P < 0.001), submucosal infiltration (OR = 2.08; 95% CI 0.84‒5.57; P = 0.125) were independent risk factors associated with metastasis. Of the 515 patients with T1N0M0 colonic NETs, the overall long-term prognosis of LE was as good as that of RS groups (after matching, 5-year CSS: 97.9% vs. 94.6%, P = 0.450; 5-year OS: 92.7% vs. 85.6%, P = 0.009).

CONCLUSION

Tumor size (11‒20 mm) and site (right colon) are associated with metastasis in T1 colonic NETs. In the absence of metastasis, LE could be a viable option for 0‒10 mm T1 colonic NETs with well/moderate differentiation in the left colon in terms of long-term survival.

Thyroid transcription factor-1 expression in lung neuroendocrine tumours: a gender-related biomarker?

PURPOSE

Thyroid transcription factor-1 (TTF-1) assessed by immunohistochemistry (IHC) is a specific biomarker for lung adenocarcinoma, and is commonly used to confirm the pulmonary origin of neuroendocrine tumours (NET). The majority of the available data suggest that TTF-1 is favourable prognostic biomarker for lung adenocarcinomas, whereas its role is more conflicting for lung NET. The main aim of this multicenter retrospective study was to investigate the potentially relevant associations between TTF-1 biomarker and clinical and pathological features of the study population, as well as determine TTF-1 prognostic effect on the clinical outcome of the patients.

METHODS

A multicentre retrospective study was conducted on 155 surgically-removed lung NET, with available IHC TTF-1 assessment.

RESULTS

Median age was 59.5 years (range 13-86), 97 patients (62.6%) were females, 31 cases (20%) were atypical carcinoids, 4 (2.6%) had TNM stage IV. Mitotic count ≥2 per 10 high-power field was found in 35 (22.6%) subjects, whereas necrosis was detected in 20 patients (12.9%). TTF-1 was positive in 78 cases (50.3%). The median overall survival was 46.9 months (range 0.6-323) and the median progression-free survival was 39.1 months (range 0.6-323). Statistically significant associations were found between (1) TTF-1 positivity and female sex (p = 0.007); and among (2) TTF-1 positivity and the absence of necrosis (p = 0.018).

CONCLUSIONS

This study highlights that TTF-1 positivity differs according to sex in lung NET, with a more common TTF-1 positive staining in female. Moreover, TTF-1 positivity correlated with the absence of necrosis. These data suggest that TTF-1 could potentially represent a gender-related biomarker for lung NET.

Case report: Radiofrequency ablation combined with biopsy for Cushing’s syndrome due to ectopic ACTH lesions in the lung

Lung carcinoid tumor is one of the major tumors causing ectopic ACTH syndrome, and the most common clinical treatment is surgical resection of the lesion. We herein report a suspected pulmonary carcinoid tumor with difficulty in surgical resection and poor response to drug therapy, which was successfully treated with radiofrequency ablation combined with intraoperative biopsy of the lesion. A 48-year-old female patient, with hypercortisolism (reddening of the face, full moon face, hirsutism, acne, and weight gain) detected three months ago. Small and high-dose dexamethasone suppression tests were not suppressed, Cushing’s syndrome was under consideration. PET-CT examination suggested mild FDG uptake in two nodules in the anterior basal segment of the lower lobe of the right lung, the possibility of ectopic ACTH lesions was considered because of the clinical presentation. Due to difficult surgical approach of the lesion, high risk of surgery and the patient’s anxiety, CT-guided thermal ablation combined with puncture biopsy was considered to treat the lesions. Image-guided thermal ablation can effectively inactivate ectopic ACTH lesions in the lung, rapidly improve the symptoms of high cortisol, and can be combined with biopsy for pathologic diagnosis. Therefore, this technique can be considered for treating pulmonary ACTH lesions that are difficult to resect surgically.

Angioside: The role of Angiogenesis and Hypoxia in Lung Neuroendocrine Tumours According to Primary Tumour Location in Left or Right Parenchyma

Well-differentiated lung neuroendocrine tumours (Lu-NETs), classified as typical (TC) and atypical (AC) carcinoids, represent 30% of NETs. Angiogenesis plays an essential role in NET development and progression. A higher vascular network is a marker of differentiation, with positive prognostic implications. Materials and Methods: We retrospectively evaluated microvessel density (MVD) by CD34 immunohistochemical (IHC) staining and hypoxia by IHC staining for Hypoxia-inducible factor 1α (HIF-1α), comparing right- and left-lung parenchyma in 53 lung NETs. Results: The median age was 66 years (39−81), 56.6% males, 24.5% AC, 40.5% left-sided tumours and 69.8% TNM stage I. The mitotic count was <2/10 per 10 HPF in 79.2%, and the absence of necrosis in 81.1%, 39.6% with Ki67, was ≤2%. The MVD, the number of vessels and the average vessel area median values were significantly higher in the right than the left parenchyma (p: 0.025, p: 0.019, p: 0.016, respectively). Hypoxia resulted present in 14/19 (73.6%) left tumours and in 10/20 (50%) right tumours in the parenchyma (p: 0.129). Conclusions: This study suggests a biological rationale for a different angiogenesis and hypoxia according to the Lu-NETs’ location. In our study, left primary tumours were less vascularized and most likely to present hypoxia than right primary tumours. This finding could have potentially useful prognostic and predictive implications for Lu-NETs.

Treatment outcome and prognostic analysis of advanced large cell neuroendocrine carcinoma of the lung

The optimal systemic treatment of advanced large cell neuroendocrine carcinoma (LCNEC) is still controversial. We intend to explore advanced LCNEC through SEER database, construct nomogram model of advanced LCNEC, and understand the effect of different treatment regimens on LCNEC. We collected 909 patients, divided them into a training set validation set, constructed nomograms using Cox proportional hazards regression models, and evaluated nomogram discrimination and calibration by C-index and calibration curves. Kaplan–Meier will also be used to compare OS in different groups of patients and to explore the impact of different treatment regimens on advanced LCNEC. On the nomogram plotted, the nomogram predicted AUC values over time were always greater than 0.7, the C-index was 0.681 (95% CI 0.656–0.706) and 0.663 (95% CI 0.628–0.698) in the training and validation sets, respectively, and patients were divided into two groups according to risk, and a significant difference in OS was observed between the high-risk and low-risk groups in the training and validation cohorts. Different treatment analyses showed that chemotherapy is still the best treatment for advanced LCNEC. This nomogram provides a convenient and reliable tool for individual assessment and clinical decision-making of patients with advanced LCNEC.