Clinicopathological characteristics, treatment and prognosis of head & neck small cell carcinoma: a SEER population-based study

Small-cell carcinoma in the head and neck region: A propensity score-matched analysis of the effect of surgery

BACKGROUND

Head and neck small-cell carcinoma (HNSmCC) is a rare and aggressive cancer with a high tendency for distant metastasis. It is treated with multimodal treatment involving chemotherapy. Occasionally, surgery is performed for the management of locoregional HNSmCC. However, the benefits of surgery in this context have not yet been elucidated. Therefore, in this study, we aimed to investigate whether surgery could improve the survival of patients with HNSmCC.

PATIENTS AND METHODS

We obtained data from patients with locoregional HNSmCC treated with chemoradiation therapy (CRT) from the Surveillance, Epidemiology, and End Results database. Patients who did and did not undergo surgery were matched using propensity scores. The overall survival (OS) and disease-specific survival (DSS) rates were estimated using the Kaplan-Meier method and tested using the log-rank test. Hazard ratios (HRs) were calculated using the Cox proportional hazard model.

RESULTS

The 5-year OS rates of the patients who did and did not undergo surgery were 57.2% and 50.6%, respectively (P = 0.689); the corresponding 5-year DSS rates were 61.0% and 57.5% (P = 0.769). The adjusted HRs for surgery were 0.85 (95% confidence interval [CI]: 0.54-1.33) for OS and 0.87 (95% CI: 0.51-1.49) for DSS.

CONCLUSION

The addition of surgery to CRT did not improve the survival of patients with locoregional HNSmCC.

Factors influencing lymph node yield in head and neck squamous cell carcinoma: A scoping review

OBJECTIVES

In head and neck cancer surgery, several studies have demonstrated the prognostic significance of lymph node yield (LNY). To our knowledge, no review has evaluated both the contributing factors to LNY and its impact on survival outcomes across all head and neck squamous cell carcinoma (HNSCC) subsites.

MATERIALS AND METHODS

A scoping review of LNY in HNSCC was conducted according to The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) framework to answer the following research questions: 1) Which surgeon, pathologist, and patient characteristics influence LNY? 2) Which anatomic subsites does LNY impact survival?

RESULTS

Surgeon experience and variation in pathology protocols and personnel can impact LNY. Extent of nodal dissection, advanced tumor characteristics, and treatment at an academic facility are associated with increased LNY. Patient characteristics such as age <40, male gender, and BMI > 30 are associated with increased LNY. In the oral cavity, LNY > 18 is an independent predictor of improved overall survival (OS), disease free survival (DFS), and disease-specific survival (DSS). In the oropharynx, published studies show mixed results with regards to the impact of LNY on OS, DFS, and DSS. LNY has not been associated with OS or DFS in the larynx, irrespective of nodal threshold.

CONCLUSIONS

Provider and patient characteristics may impact LNY. LNY ≥ 18 is associated with a survival benefit in the oral cavity and HNSCC overall. Further investigation of LNY particularly in prospective clinical trials is required prior to its adoption as a quality metric in HNSCC.

Prognosis Prediction in Head and Neck Squamous Cell Carcinoma by Radiomics and Clinical Information

(1) Background: head and neck squamous cell carcinoma (HNSCC) is a common cancer whose prognosis is affected by its heterogeneous nature. We aim to predict 5-year overall survival in HNSCC radiotherapy (RT) patients by integrating radiomic and clinical information in machine-learning models; (2) Methods: HNSCC radiotherapy planning computed tomography (CT) images with RT structures were obtained from The Cancer Imaging Archive. Radiomic features and clinical data were independently analyzed by five machine-learning algorithms. The results were enhanced through a voted ensembled approach. Subsequently, a probability-weighted enhanced model (PWEM) was generated by incorporating both models; (3) Results: a total of 299 cases were included in the analysis. By receiver operating characteristic (ROC) curve analysis, PWEM achieved an area under the curve (AUC) of 0.86, which outperformed both radiomic and clinical factor models. Mean decrease accuracy, mean decrease Gini, and a chi-square test identified T stage, age, and disease site as the most important clinical factors in prognosis prediction; (4) Conclusions: our radiomic-clinical combined model revealed superior performance when compared to radiomic and clinical factor models alone. Further prospective research with a larger sample size is warranted to implement the model for clinical use.

Long-term outcomes and prognosis of neuroendocrine neoplasms of the head and neck: a cohort from a single institution

BACKGROUND

Neuroendocrine neoplasm is a rare cancer of head and neck. This study aimed to evaluate clinical features, treatment outcomes, and prognostic factors of neuroendocrine neoplasm of head and neck treated at a single institution.

METHODS

Between Nov 2000 and Nov 2021, ninety-three patients diagnosed with neuroendocrine neoplasms of head and neck treated at our institution were reviewed retrospectively. The initial treatments included chemotherapy (induction, adjuvant, or concurrent) combined with radiotherapy in 40 patients (C + RT group), surgery followed by post-operative RT in 34 (S + RT group), and surgery plus salvage therapy in 19 patients (S + Sa group).

RESULTS

The median follow-up time was 64.5 months. 5-year overall survival rate (OS), progression-free survival rate (PFS), loco-regional relapse-free survival free rate (LRRFS) and distant metastasis-free survival rate (DMFS) were 64.5%, 51.6%, 66.6%, and 62.1%, respectively. For stage I-II, the 5-year LRRFS for patients' treatment regimen with or without radiotherapy (C + RT and S + RT groups versus S + Sa group) was 75.0% versus 12.7% (p = 0.015) while for stage III-IV, the 5-year LRRFS was 77.8% versus 50.0% (p = 0.006). The 5-year DMFS values for patients with or without systemic therapy (C + RT group versus S + RT or S + Sa) were 71.2% and 51.5% (p = 0.075). 44 patients (47.3%) experienced treatment failure and distant metastasis was the main failure pattern.

CONCLUSIONS

Radiotherapy improved local-regional control and played an important role in the management of HNNENs. The optimal treatment regimen for HNNENs remains the combination of local and systemic treatments.

A Random Forest Model for Post-Treatment Survival Prediction in Patients with Non-Squamous Cell Carcinoma of the Head and Neck

BACKGROUND

Compared to squamous cell carcinoma, head and neck non-squamous cell carcinoma (HNnSCC) is rarer. Integrated survival prediction tools are lacking.

METHODS

4458 patients of HNnSCC were collected from the SEER database. The endpoints were overall survivals (OSs) and disease-specific survivals (DSSs) of 3 and 5 years. Cases were stratified-randomly divided into the train & validation (70%) and test cohorts (30%). Tenfold cross validation was used in establishment of the model. The performance was evaluated with the test cohort by the receiver operating characteristic, calibration, and decision curves.

RESULTS

The prognostic factors found with multivariate analyses were used to establish the prediction model. The area under the curve (AUC) is 0.866 (95%CI: 0.844-0.888) for 3-year OS, 0.862 (95%CI: 0.842-0.882) for 5-year OS, 0.902 (95%CI: 0.888-0.916) for 3-year DSS, and 0.903 (95%CI: 0.881-0.925) for 5-year DSS. The net benefit of this model is greater than that of the traditional prediction methods. Among predictors, pathology, involved cervical nodes level, and tumor size are found contributing the most variance to the prediction. The model was then deployed online for easy use.

CONCLUSIONS

The present study incorporated the clinical, pathological, and therapeutic features comprehensively and established a clinically effective survival prediction model for post-treatment HNnSCC patients.

An online tool for survival prediction of extrapulmonary small cell carcinoma with random forest

Purpose

Extrapulmonary small cell carcinoma (EPSCC) is rare, and its knowledge is mainly extrapolated from small cell lung carcinoma. Reliable survival prediction tools are lacking.

Methods

A total of 3,921 cases of EPSCC were collected from the Surveillance Epidemiology and End Results (SEER) database, which form the training and internal validation cohorts of the survival prediction model. The endpoint was an overall survival of 0.5-5 years. Internal validation performances of machine learning algorithms were compared, and the best model was selected. External validation (n = 68) was performed to evaluate the generalization ability of the selected model.

Results

Among machine learning algorithms, the random forest model performs best on internal validation, whose area under the curve (AUC) is 0.736-0.800. The net benefit is higher than the TNM classification in decision curve analysis. The AUC of this model on the external validation cohort is 0.739-0.811. This model was then deployed online as a free, publicly available prediction tool of EPSCC (http://42.192.80.13:4399/).

Conclusion

This study provides an excellent online survival prediction tool for EPSCC with machine learning and large-scale data. Age, TNM stages, and surgery (including potential performance status information) are the most critical factors for the prediction model.

Head and neck small-cell carcinoma: A multicenter study of 39 cases from 10 institutions

Objective

Basal information of head and neck small-cell carcinoma (HNSmCC) including epidemiology, primary site, treatment, and prognosis remains sparse due to its rarity. We report here a multicenter retrospective study on the diagnosis, treatment, and outcomes of patients with HNSmCC.

Materials and methods

This study involved 47 patients with HNSmCC from 10 participating institutions. Eight patients were excluded for whom no pathological specimens were available (n = 2) and for discrepant central pathological judgements (n = 6). The remaining 39 patients were processed for data analysis.

Results

As pretreatment examinations, computed tomography (CT) was performed for the brain (n = 8), neck (n = 39), and chest (n = 32), magnetic resonance imaging (MRI) for the brain (n = 4) and neck (n = 23), positron emission tomography-CT (PET-CT) in 23 patients, bone scintigraphy in 4, neck ultrasonography in 9, and tumor markers in 25. Primary sites were oral cavity (n = 1), nasal cavity/paranasal sinuses (n = 16), nasopharynx (n = 2), oropharynx (n = 4), hypopharynx (n = 2), larynx (n = 6), salivary gland (n = 3), thyroid (n = 2), and others (n = 3). Stages were II/III/IV-A/IV-B/IV-C/Not determined = 3/5/16/6/5/4; stage IV comprised 69%. No patient had brain metastases. First-line treatments were divided into 3 groups: the chemoradiotherapy (CRT) group (n = 27), non-CRT group (n = 8), and best supportive care group (n = 4). The CRT group included concurrent CRT (CCRT) (n = 17), chemotherapy (Chemo) followed by radiotherapy (RT) (n = 5), and surgery (Surg) followed by CCRT (n = 5). The non-CRT group included Surg followed by RT (n = 2), Surg followed by Chemo (n = 1), RT alone (n = 2), and Chemo alone (n = 3). The 1-year/2-year overall survival (OS) of all 39 patients was 65.3/53.3%. The 1-year OS of the CRT group (77.6%) was significantly better compared with the non-CRT group (31.3%). There were no significant differences in adverse events between the CCRT group (n = 22) and the Chemo without concurrent RT group (n = 9).

Conclusion

Neck and chest CT, neck MRI, and PET-CT would be necessary and sufficient examinations in the diagnostic set up for HNSmCC. CCRT may be recommended as the first-line treatment. The 1-year/2-year OS was 65.3%/53.3%. This study would provide basal data for a proposing the diagnostic and treatment algorithms for HNSmCC.

Malignant Myoepithelioma of the Head and Neck: Demographics, Clinicopathological Characteristics, Treatment, and Prognosis

Malignant myoepithelioma of the head and neck (HNMM) is a rare malignancy, and its characteristics and survival rates have not been well-defined. This study aimed to define the epidemiology of HNMM and identify the prognostic factors associated with the disease. Data on all patients diagnosed with HNMM between 1991 and 2016 were gathered from the Surveillance Epidemiology and End Results (SEER) database. The demographics, clinicopathological characteristics, treatment, and prognoses of the patients were described. Cox regression analysis was used to identify the prognostic factors, and the prognostic nomograms for overall survival (OS) and disease-specific survival (DSS) were constructed. A total of 333 cases of HNMM were identified. The average age at diagnosis was 60.6 years, and 50.1% of the patients were men. After diagnosis, 46.2% of patients underwent surgery alone, 43.5% of patients underwent surgery and radiotherapy, and 3.6% of patients received only radiotherapy. Survival analysis showed that the 5-year OS and DSS for all HNMM patients were 69.7 and 82.1%, respectively. In the multivariate analysis model, the undifferentiated pathological grade (P <0.05) and M1 in the M category (P <0.01) were independent prognostic factors for poor OS and DSS, whereas the use of surgical resection was an independent favorable prognostic factor for both OS and DSS (P <0.05). The prognostic nomograms for OS and DSS prediction were constructed; the C-index values for OS and DSS prediction were 0.78 (95% CI 0.70–0.86) and 0.79 (95% CI 0.67–0.90), respectively. In conclusion, this SEER data-based study demonstrated that HNMM patients often had a favorable prognosis, and distant metastasis, pathological grade, and the use of surgery contributed to their survival. Furthermore, we developed a prognostic nomogram to predict OS and DSS for HNMM patients to aid physicians in the clinical management of this rare disease.

A Novel Overall Survival Nomogram Prediction of Secondary Primary Malignancies after Hypopharyngeal Cancer: A Population-Based Study

Objectives

We aimed to construct a nomogram for predicting the overall survival (OS) of patients with secondary primary malignancies (SPMs) after hypopharyngeal cancer (HPC).

Methods

613 HPC patients were included in the Surveillance, Epidemiology, and End Results (SEER) database between 2000 and 2018, which were divided into training and validation cohorts. The least absolute shrinkage and selection operation (LASSO) and stepwise Cox regression were used to determine the variables by which a nomogram model was established.

Results

After the LASSO and stepwise Cox regression analysis, the age, year of diagnosis, sites of SPMs, SEER stage of SPMs, surgery for SPMs, and radiotherapy for SPMs were included for model establishment. The ROC curve showed good discrimination for the 3- and 5-year AUC values in the training (0.774 and 0.779, respectively) and validation (0.758 and 0.763, respectively) cohorts. The calibration curve indicated good prognostic accuracy, especially in the 5-year survival prediction for this model. The DCA also demonstrated clinical efficacy over a wide range of threshold probabilities. Lastly, the risk group classified by the individual nomogram values showed significantly different survival outcomes in both training and validation cohorts.

Conclusions

We constructed a nomogram to predict the OS of SPMs after HPC with good clinical values.

Survival and risk factors of adenosquamous carcinoma in the oral and maxillofacial region: a population-based study

BACKGROUND

The features and prognosis of adenosquamous carcinoma (ASC) in oral and maxillofacial region have not thoroughly investigated, the purpose of this study is to describe clinicopathologic characteristics, treatment, and prognostic factors of this disease.

METHODS

The data of 276 patients diagnosed with ASC in oral and maxillofacial region between 1975 and 2016 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. The prognostic factors influencing overall survival (OS) and disease-specific survival (DSS) were identified by the Kaplan-Meier analysis and Cox regression analysis. The nomograms for OS and DSS were constructed to predict the prognosis of these patients.

RESULTS

Of 276 included patients, 62.7% were male and 37.3% were female, with an average age at diagnosis of 63.5 years. The most common primary site is oral cavity (170/276), followed by salivary gland (106/276). The 3-, and 5-year OS of patients with ASC in oral and maxillofacial region were 49.0% and 38.9%, while the 3-, and 5-year DSS were 67.7%, and 60.4%, respectively. Patients who underwent surgery had longer OS (mOS: 58 m vs. 8 m) and DSS (mDSS: 193 m vs. 18 m) than those who did not. Age, AJCC-T/N/M category as well as surgery were independently associated with OS. Advanced T stage, distant metastases, and surgery were independent factors for DSS. The prognostic nomograms for OS and DSS were constructed, and the C-indexes were 0.71 (95% CI 0.66-0.76) and 0.76 (95% CI 0.67-0.85), respectively.

CONCLUSION

Surgery was the favorable prognostic factor for both OS and DSS among patients with ASC in oral and maxillofacial region.

Neuroendocrine Carcinoma of the Larynx and Pharynx: A Clinical and Histopathological Study

Simple Summary

Neuroendocrine carcinomas (NECs) of the head and neck are rare. The presented series of 20 patients with laryngeal and pharyngeal NECs is population-based and one of the largest published to date. We analyzed the treatment results according to the type of therapy and the role of various standard (synaptophysin-chromogranin-CD56, Ki-67, p16, HPV, and EBV) and some novel (INSM1 and PD-L1) neuroendocrine markers or potential prognosticators. The results indicate the following: (1) laryngeal and pharyngeal NECs accounted for 0.43% and 0.17% of the cases in the corresponding tumor groups, respectively; (2) neuroendocrine differentiation can be reliably determined by INSM1 immunohistochemistry; (3) the prognosis was determined by the nodal stage and TNM stage but not by the histological grade (which refers to moderately and poorly differentiated NECs); (4) except in well-differentiated NECs and early-stage (T1-2N0-1) moderately/poorly differentiated NECs, aggressive multimodal therapy is needed; and (5) the p16, HPV, and EBV statuses failed to show any prognostic value.

Abstract

Neuroendocrine carcinomas (NECs) of the head and neck are rare and the experience scanty. The Cancer Registry of Slovenia database was used to identify cases of laryngeal and pharyngeal NECs diagnosed between 1995–2020. Biopsies were analyzed for the expression of standard neuroendocrine markers (synaptophysin, chromogranin, CD56), INSM1, Ki-67, p16, and PD-L1 (using the combined positive score, CPS). In situ hybridization for human papillomavirus (HPV) and Epstein–Barr virus (EBV) was performed. Twenty patients (larynx, 12; pharynx, 8) were identified. One tumor was well differentiated (WD), five were moderately differentiated (MD), and 14 were poorly differentiated (PD). Disease control was achieved solely by surgery in 4/4 MD/PD T1-2N0-1 tumors. Eight patients died of the disease, seven of which were due to distant metastases. All three traditional markers were positive in 11/17 NECs and the INSM1 marker in all 20 tumors. Two of fourteen p16-positive tumors were HPV-positive, but all three nasopharyngeal NECs were EBV-negative. Three tumors had CPSs ≥ 1. In conclusion, INSM1 was confirmed to be a reliable marker of neuroendocrine differentiation. Except in WD and early-stage MD/PD tumors, aggressive multimodal therapy is needed; the optimal systemic therapy remains to be determined. p16, HPV, and EBV seem to bear no prognostic information.