A Histopathologic Scoring System for Perineural Invasion Correlates With Adverse Outcomes in Patients With Cutaneous Squamous Cell Carcinoma

Extensive Perineural Invasion vs Nerve Caliber to Assess Cutaneous Squamous Cell Carcinoma Prognosis

Importance

Perineural invasion (PNI) is an adverse risk feature in cutaneous squamous cell carcinoma (CSCC) that affects patient prognosis and disease management. However, research comparing different PNI patterns on patient outcomes is limited.

Objective

To compare 4 assessments of PNI in CSCC, their associations with poor outcomes, and implications for their inclusion in the Brigham and Women's Hospital (BWH) staging system.

Design, Setting, and Participants

This retrospective cohort study was performed at a single tertiary care institution and compared 4 PNI assessments: nerve caliber, number of involved nerves per section, PNI maximal depth, and PNI location with respect to tumor. Patients with primary, localized, invasive CSCC with PNI diagnosed between January 1, 2000, and December 31, 2017, were identified via an electronic in-house database. Available pathology slides were secondarily reviewed by study authors. Relevant patient and tumor characteristics and outcomes were abstracted from the medical record. Data analysis was performed between September 6 and October 20, 2022.

Main Outcomes and Measures

Risks of recurrence, disease-specific death, and a composite end point (any poor outcome) were calculated via multivariable stepwise Fine and Gray competing-risks regression. Considered revisions to the BWH staging system were assessed via receiver operating characteristic curves and test characteristics.

Results

This study included 140 patients with CSCC, with a mean (SD) age of 75.1 (11.2) years. More than half of the patients were men (93 [66.4%]), and most identified as White (132 [94.3%]). Of the 4 PNI assessments studied, only involvement of multiple nerves was associated with poor outcomes. Perineural invasion of 5 or more distinct nerves (extensive PNI [ePNI]) was independently associated with local recurrence (subhazard ratio [SHR], 13.83 [95% CI, 3.50-54.62]; P < .001), disease-specific death (SHR, 6.20 [95% CI, 1.59-24.21]; P = .009), and any poor outcome (SHR, 10.21 [95% CI, 2.88-36.15]; P < .001). A revised BWH staging system with substitution of ePNI for large-caliber PNI resulted in improved area under the curve and test characteristics compared with current BWH staging criteria that use nerve caliber as the measure of PNI.

Conclusions and Relevance

The findings of this cohort study suggest that ePNI is the best prognostic measure of PNI. Because ePNI obviated the need for a micrometer and had superior prognostic capacity to nerve caliber in this cohort, ePNI should be considered for inclusion in CSCC tumor staging. Inclusion of ePNI as a high-risk factor in CSCC staging systems may optimize patient selection for primary treatment and adjuvant interventions.

Recommendations for risk stratification of periocular squamous cell carcinoma

Periocular squamous cell carcinoma is a common cutaneous malignancy with generally favorable outcomes; however, the periocular region is intrinsically a high-risk location, and there exist a subset of lesions with a propensity for poor outcomes. Orbital invasion, intracranial perineural spread, nodal and distant metastasis are feared complications. There are several staging systems for eyelid carcinoma and cutaneous squamous cell carcinoma, but the definition of high-risk lesions remains heterogeneous. It is unclear exactly which lesions can be safely deescalated, and which require nodal evaluation and adjuvant multimodal therapy. We seek to answer these questions by summarizing the literature on clinicopathologic variables, molecular markers, and gene profiling tests in periocular squamous cell carcinoma, with the extrapolation of data from the cutaneous squamous cell carcinoma literature. Standardized pathology reports with information on tumor dimensions, histological subtype and grade, perineural invasion, and lymphovascular invasion should become uniform. Integration with gene expression profiling assessments will individualize and improve the predictive accuracy of risk stratification tools to ultimately inform multidisciplinary decision-making.

Perineural invasion and perineural spread in periocular squamous cell carcinoma

Perineural invasion (PNI) in cutaneous squamous cell carcinoma (SCC) of the periocular region is a prognostic marker of adverse tumour outcomes. PNI carries a well-established risk of tumour recurrence, regional metastasis and higher likelihood of mortality. This review will explore and stratify the risks conferred by histological PNI parameters. The radiological features of perineural spread (PNS) and the imaging sequences that delineate these findings will also be highlighted. Surgical excision with en face margin control is the preferred technique for achieving histological clearance. Adjuvant radiotherapy improves treatment outcomes in the setting of concomitant high-risk features. For locally advanced or metastatic cutaneous SCC, immunotherapy represents a novel treatment alternative. This review will provide an algorithm for the diagnosis and management of periocular SCC with PNI and PNS.

The value of 18F-FDG PET/CT-based radiomics in predicting perineural invasion and outcome in non-metastatic colorectal cancer

PURPOSE

Perineural invasion (PNI) has been recognized as an important prognosis factor in patients with colorectal cancer (CRC). The purpose of this retrospective study was to investigate the value of ¹⁸F-FDG PET/CT-based radiomics integrating clinical information, PET/CT features, and metabolic parameters for preoperatively predicting PNI and outcome in non-metastatic CRC and establish an easy-to-use nomogram.

METHODS

A total of 131 patients with non-metastatic CRC who undergo PET/CT scan were retrospectively enrolled. Univariate analysis was used to compare the differences between PNI-present and PNI-absent groups. Multivariate logistic regression was performed to select the independent predictors for PNI status. Akaike information criterion (AIC) was used to select the best prediction models for PNI status. CT radiomics signatures (RSs) and PET-RSs were selected by maximum relevance minimum redundancy (mRMR) and the least absolute shrinkage and selection operator algorithm (LASSO) regression and radiomics scores (Rad-scores) were calculated for each patient. The prediction models with or without Rad-score were established. According to the nomogram, nomogram scores (Nomo-scores) were calculated for each patient. The performance of different models was assessed with the area under the curve (AUC), specificity, and sensitivity. The clinical usefulness was assessed by decision curve (DCA). Multivariate Cox regression was used to selected independent predictors of progression-free survival (PFS).

RESULTS

Among all the clinical information, PET/CT features, and metabolic parameters, CEA, lymph node metastatic on PET/CT (N stage), and total lesion glycolysis (TLG) were independent predictors for PNI (p < 0.05). Six CT-RSs and 12 PET-RSs were selected as the most valuable factors to predict PNI. The Rad-score calculated with these RSs was significantly different between PNI-present and PNI-absent groups (p < 0.001). The AUC of the constructed model was 0.90 (95%CI: 0.83-0.97) in the training cohort and 0.80 (95%CI: 0.65-0.95) in the test cohort. The nomogram's predicting sensitivity was 0.84 and the specificity was 0.83 in the training cohort. The clinical model's predicting sensitivity and specificity were 0.66 and 0.85 in the training cohort, respectively. Besides, DCA showed that patients with non-metastatic CRC could get more benefit with our model. The results also indicated that N stage, PNI status, and the Nomo-score were independent predictors of PFS in patients with non-metastatic CRC.

CONCLUSION

The nomogram, integrating clinical data, PET/CT features, metabolic parameters, and radiomics, performs well in predicting PNI status and is associated with the outcome in patients with non-metastatic CRC.