Age-related Differences in Tumour Characteristics and Prognostic Factors for Disease Progression in Cutaneous Squamous Cell Carcinoma of the Head and Neck

Metastatic patterns and treatment options for head and neck cutaneous squamous cell carcinoma (Review)

According to current predictions, one-fifth of all Americans will develop skin cancer during their lifetime. Cutaneous squamous cell carcinoma (cSCC) most commonly occurs in the head and neck region, which is the area of the body with the highest level of sun exposure. High-risk head and neck cSCC (HNcSCC) is a broad category with numerous high-risk factors that are associated with unfavorable results. In cSCC staging systems, clinical and tumor traits that are likely to result in poor outcomes are identified. Metastasis occurs in ~2.5% of patients with cSCC, most often in the local lymph nodes, and there is some indication that lymph node metastasis has a distinct pattern based on the tumor site. Current findings on tumor molecular targets have suggested the use of systemic treatments, particularly immunotherapy (such as cemiplimab, pembrolizumab and nivolumab), over radiotherapy or chemotherapy for this type of metastasis. However, when used simultaneously with immunotherapy, radiotherapy may be beneficial in the treatment of metastatic HNcSCC by improving the efficacy of immunotherapy. The present review aims to assess the existing literature on metastatic HNcSCC pathways and treatment options, in order to define current and future directions. Notably, there is an urgent need to identify patients who may benefit from local or systemic cancer treatments. The treatment of lymph node metastasis presents a therapeutic challenge and requires comprehensive management.

Risk factors and novel predictive model for metastatic cutaneous squamous cell carcinoma: a population-based analysis

Cutaneous squamous cell carcinoma (cSCC) is one of the most common skin malignancies. Patients with metastatic cSCC (mcSCC) tended to have unfavorable prognosis. However, there is no available models to evaluate the survival outcomes for these patients. This study retrospectively collected mcSCC cases identified from The Surveillance, Epidemiology, and End Results (SEER) database from 2000 to 2018. All patients were randomly divided into the training and validation cohorts. The independent factors which predicted the cancer-specific survival (CSS) were identified by Cox proportional hazard regression analysis, and were used to build nomogram. he discrimination ability of nomograms was evaluated using the concordance index (C-index). The receiver operating characteristic (ROC) curve and the corresponding area under the curve (AUC) at 1, 3, and 5 years were calculated to estimate the predictive accuracy. The performance of this nomogram was evaluated by the calibration curves. The decision curve analyses (DCAs) were conducted to assess the clinical usefulness of the models. Based on the novel nomograms, all patients were classified into low- and high-risk groups. Kaplan-Meier curves were plotted to compare the survival outcomes of two groups. All analyses were conducted by R software (Version 4.1.3). A total of 916 patients were included. Age, marital status, location of the primary sites, number of metastases, T stage, N stage, surgical resection of the primary sites, radiotherapy of the primary sites, and chemotherapy were significantly associated with CSS. A nomogram predicting CSS was built based on these parameters. C-index and ROC curves of nomogram showed promising discriminating and predicting ability for CSS. Survival analysis showed that patients in the low-risk group had significant superior CSS time than those in the high-risk group (median CSS time: 15.0 vs. 5.0 months, p < 0.001). In conclusion, we developed and validated a novel nomogram predicting the CSS in metastatic cSCC patients. This nomogram could be used to assess the prognosis of metastatic cSCC patients, and help clinicians evaluating optimal treatment options for individual patient.

Personalised decision making to predict absolute metastatic risk in cutaneous squamous cell carcinoma: development and validation of a clinico-pathological model

Background

Cutaneous squamous cell carcinoma (cSCC) is a common skin cancer, affecting more than 2 million people worldwide yearly and metastasising in 2-5% of patients. However, current clinical staging systems do not provide estimates of absolute metastatic risk, hence missing the opportunity for more personalised treatment advice. We aimed to develop a clinico-pathological model that predicts the probability of metastasis in patients with cSCC.

Methods

Nationwide cohorts from (1) all patients with a first primary cSCC in The Netherlands in 2007-2008 and (2) all patients with a cSCC in 2013-2015 in England were used to derive nested case-control cohorts. Pathology records of primary cSCCs that originated a loco-regional or distant metastasis were identified, and these cSCCs were matched to primary cSCCs of controls without metastasis (1:1 ratio). The model was developed on the Dutch cohort (n = 390) using a weighted Cox regression model with backward selection and validated on the English cohort (n = 696). Model performance was assessed using weighted versions of the C-index, calibration metrics, and decision curve analysis; and compared to the Brigham and Women's Hospital (BWH) and the American Joint Committee on Cancer (AJCC) staging systems. Members of the multidisciplinary Skin Cancer Outcomes (SCOUT) consortium were surveyed to interpret metastatic risk cutoffs in a clinical context.

Findings

Eight out of eleven clinico-pathological variables were selected. The model showed good discriminative ability, with an optimism-corrected C-index of 0.80 (95% Confidence interval (CI) 0.75-0.85) in the development cohort and a C-index of 0.84 (95% CI 0.81-0.87) in the validation cohort. Model predictions were well-calibrated: the calibration slope was 0.96 (95% CI 0.76-1.16) in the validation cohort. Decision curve analysis showed improved net benefit compared to current staging systems, particularly for thresholds relevant for decisions on follow-up and adjuvant treatment. The model is available as an online web-based calculator (https://emc-dermatology.shinyapps.io/cscc-abs-met-risk/).

Interpretation

This validated model assigns personalised metastatic risk predictions to patients with cSCC, using routinely reported histological and patient-specific risk factors. The model can empower clinicians and healthcare systems in identifying patients with high-risk cSCC and offering personalised care/treatment and follow-up. Use of the model for clinical decision-making in different patient populations must be further investigated.

Funding

PPP Allowance made available by Health-Holland, Top Sector Life Sciences & Health, to stimulate public-private partnerships.

Association of Patient Risk Factors, Tumor Characteristics, and Treatment Modality With Poor Outcomes in Primary Cutaneous Squamous Cell Carcinoma: A Systematic Review and Meta-analysis

Importance

Primary cutaneous squamous cell carcinoma is usually curable; however, a subset of patients develops poor outcomes, including local recurrence, nodal metastasis, distant metastasis, and disease-specific death.

Objectives

To evaluate all evidence-based reports of patient risk factors and tumor characteristics associated with poor outcomes in primary cutaneous squamous cell carcinoma and to identify treatment modalities that minimize poor outcomes.

Data Sources

PubMed, Embase, and SCOPUS databases were searched for studies of the topic in humans, published in the English language, from database inception through February 8, 2022.

Study Selection

Two authors independently screened the identified articles and included those that were original research with a sample size of 10 patients or more and that assessed risk factors and/or treatment modalities associated with poor outcomes among patients with primary cutaneous squamous cell carcinoma.

Data Extraction and Synthesis

Data extraction was performed by a single author, per international guidelines. The search terms, study objectives, and protocol methods were defined before study initiation. A total of 310 studies were included for full-text assessment. Owing to heterogeneity of the included studies, a random-effects model was used. Data analyses were performed from May 25 to September 15, 2022.

Main Outcomes and Measures

For studies of risk factors, risk ratios and incidence proportions; and for treatment studies, incidence proportions.

Results

In all, 129 studies and a total of 137 449 patients with primary cutaneous squamous cell carcinoma and 126 553 tumors were included in the meta-analysis. Several patient risk factors and tumor characteristics were associated with local recurrence, nodal metastasis, distant metastasis, disease-specific death, and all-cause death were identified. Among all factors reported by more than 1 study, the highest risks for local recurrence and disease-specific death were associated with tumor invasion beyond subcutaneous fat (risk ratio, 9.1 [95% CI, 2.8-29.2] and 10.4 [95% CI, 3.0- 36.3], respectively), and the highest risk of any metastasis was associated with perineural invasion (risk ratio, 5.0; 95% CI, 2.3-11.1). Patients who received Mohs micrographic surgery had the lowest incidence of nearly all poor outcomes; however, in some results, the 95% CIs overlapped with those of other treatment modalities.

Conclusions and Relevance

This meta-analysis identified the prognostic value of several risk factors and the effectiveness of the available treatment modalities. These findings carry important implications for the prognostication, workup, treatment, and follow-up of patients with primary cutaneous squamous cell carcinoma.

Trial Registration

PROSPERO Identifier: CRD42022311250.

The Effect of Tumor Characteristics and Location on the Extent of Lymph Node Metastases of Head and Neck Cutaneous Squamous Cell Carcinoma

Background

The extent of a neck dissection for patients with metastasis of cutaneous squamous cell carcinoma of the head and neck (HNcSCC) is still subject to debate and clear guidelines are lacking. Tumor characteristics like size, differentiation and tumor location are known risk factors for lymph node metastasis (LNM). There is some evidence that, depending on tumor location, LNM follows a specific pattern. This study aims to identify which tumor characteristics can predict the pattern and extent of LNM.

Method

In this cohort study 80 patients were included, who underwent a primary neck dissection for LNM of HNcSCC between 2003 and 2018 at the University Medical Center Groningen, the Netherlands. Retrospective data was collected for primary tumor characteristics and LNM and included surgical and follow-up data. Influence of tumor characteristics on the extent of LNM was analyzed using non-parametric tests. Logistic regression analysis were used to identify a metastasis pattern based on the primary tumor location.

Results

Only primary tumor location was associated with the pattern of LNM. HNcSCC of the ear metastasized to level II (OR = 2.6) and the parotid gland (OR = 3.6). Cutaneous lip carcinoma metastasized to ipsilateral and contralateral level I (OR = 5.3). Posterior scalp tumors showed a metastasis pattern to level II (OR = 5.6); level III (OR = 11.2), level IV (OR = 4.7) and the parotid gland (OR = 10.8). Ear canal tumors showed a low risk of LNM for all levels. The extent of LNM was not related to age or any tumor characteristics i.e. tumor diameter, infiltration depth, differentiation grade, perineural growth and vascular invasion.

Conclusion

Primary tumor location determines the LNM pattern. Whereas known unfavorable tumor characteristics did not relate to the extent of LNM. Location guided limited neck dissection combined with parotidectomy will treat most patients adequately.