Different mitotic rates are associated with different prognostic factors, relapses, and survival rates in melanoma

Impact of COVID-19 Pandemic on Delay of Melanoma Diagnosis: A Systematic Review and Meta-Analysis

INTRODUCTION

Several studies have described how the restrictive measures due to COVID-19 have delayed melanoma diagnoses, resulting in an increased rate of more severe cases. Summarizing the sparse results in this context might help to understand the real impact of the COVID-19 pandemic on melanoma. We conducted a systematic review and meta-analysis to investigate how the clinical and prognostic factors of new melanoma diagnoses changed after COVID-19.

METHODS

A literature search in MEDLINE, EMBASE, and Scopus was conducted in September 2023. We included studies published in peer-reviewed journals reporting histopathological data on new diagnoses of cutaneous melanoma in adult patients during and/or after the lockdown compared to those diagnosed before the COVID-19 pandemic. A meta-analysis was conducted utilizing a random effects model. The between-study heterogeneity was assessed via Higgins's I2 statistic. Publication bias was assessed using the Begg and Egger test. This study adhered to the updated PRISMA guidelines. The primary outcome was a comparison of melanoma thickness between the pre-COVID-19 and post-lockdown periods. The secondary outcomes were evaluations of the histopathological subtype, stage, and presence of ulceration and mitosis in melanomas diagnosed in these two pandemic phases.

RESULTS

The study included 45 articles. We found a significantly higher proportion of all factors indicating worse prognosis in the post-lockdown period compared to the pre-COVID-19 phase, including high thickness (SOR = 1.14, 95%CI 1.08-1.20 for 1-2 mm; SOR = 1.62, 95%CI 1.08-2.40, for >2 mm), the presence of ulcerations (SOR = 1.35, 95%CI 1.18-1.54), nodular subtype (SOR = 1.19, 95%CI 1.07-1.32), the presence of mitosis (SOR = 1.57, 95% CI 1.17-2.11), and stage III (SOR = 1.39, 95%CI 1.19-1.52) and IV (SOR = 1.44, 95%CI 1.26-1.63). Limitations include the limited studies' geographical distribution and moderate heterogeneity affecting meta-analysis estimates.

CONCLUSIONS

Our meta-analysis provided evidence of more advanced melanomas diagnosed in the post-COVID-19 pandemic period, emphasizing the importance of creating and updating pandemic preparedness plans to limit the impact of any future events on oncological care.

Diagnostic and prognostic risk factors analysis for distant metastasis in melanoma: a population-based study

BACKGROUND

We aimed to develop tools that could predict the occurrence of distant metastases in melanoma and its prognosis based on clinical and pathological characteristics.

MATERIALS AND METHODS

We obtained data from the Surveillance, Epidemiology, and End Results (SEER) database of melanoma patients diagnosed between 2010 and 2019. Logistic analyses were performed to identify independent risk factors associated with distant metastasis. Additionally, multivariate Cox analyses were conducted to determine independent prognostic factors for patients with distant metastasis. Two nomograms were established and evaluated with the receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Furthermore, we performed a retrospective analysis of melanoma with distant metastasis from our institute between March 2018 and June 2022.

RESULTS

Of the total 19 396 melanoma patients, 352 (1.8%) had distant metastases at the time of diagnosis. The following clinical and pathological characteristics were identified as independent risk factors for distant metastasis in melanoma: N stage, tumor size, ulceration, mitosis, primary tumor site, and pathological subtype. Furthermore, tumor size, pathological subtype, and radiotherapy were identified as independent prognostic factors. The results of the training and validation cohorts' ROC curves, calibration, DCA, and Kaplan-Meier survival curves demonstrate the effectiveness of the two nomograms. The retrospective study results from our center supported the results from the SEER database.

CONCLUSION

The clinical and pathological characteristics of melanoma can predict a patient's risk of metastasis and prognosis, and the two nomograms are expected to be effective tools to guide therapy decisions.

Melanoma with rhabdomyosarcomatous features: a potential diagnostic pitfall

Malignant melanoma is well-known for phenotypic plasticity, and rare cases of divergent differentiation have been described. This case report is of a tumour diagnosed as 'rhabdomyosarcoma' on the face of a man in his 80s. However, given the recent excision of an ulcerated melanoma (Breslow thickness 5.8 mm) from the same site, the more likely diagnosis would be recurrent melanoma with rhabdomyosarcomatous differentiation. This highlights a rare form of divergent differentiation and a potential diagnostic pitfall.

Predictive accuracy of elevated mitotic rate on lymph node positivity and recurrence in thin melanomas

Background

Mitotic rate (MR) is considered an important prognostic factor for melanoma but is not currently used for staging because its nuanced effect is not yet well-delineated. We sought to determine if T category-specific MR is predictive of sentinel lymph node (SLN) positivity, recurrence, and melanoma-specific mortality (MSM).

Methods

A retrospective review of patients with primary cutaneous melanoma from 1994 to 2020 at a single academic center was performed. Patient demographics and tumor characteristics were recorded. MR was considered elevated for each AJCC8-defined T category if it was ≥2 mitoses/mm² for T1, ≥4 mitoses/mm² for T2, ≥6 mitoses/mm² for T3, or ≥7 mitoses/mm² for T4. Statistical analysis was performed to assess the predictive accuracy of MR on selected outcomes while controlling for ulceration.

Results

Data from 2,984 patients with complete records were analyzed. Along with Breslow thickness and ulceration, elevated MR was associated with higher risk of MSM (HR 1.816, P=0.0001). There was no difference among patients with ulcerated T1 or T2 tumors regardless of MR, but those with non-ulcerated T1 or T2 tumors and elevated MR were more likely to have positive SLNs (P<0.0001 and P=0.0043, respectively) and recurrence (P=0.0007 and P=0.0004, respectively) compared to counterparts with low MR. There were no notable differences for T3 or T4 tumors based on MR.

Conclusions

Elevated MR is associated with SLN positivity and recurrence in thin melanomas, independent of ulceration. SLN biopsy should therefore be strongly considered for patients with non-ulcerated lesions <0.8 mm thick if the MR is ≥2 mitoses/mm².

Prediction of early-stage melanoma recurrence using clinical and histopathologic features

Prognostic analysis for early-stage (stage I/II) melanomas is of paramount importance for customized surveillance and treatment plans. Since immune checkpoint inhibitors have recently been approved for stage IIB and IIC melanomas, prognostic tools to identify patients at high risk of recurrence have become even more critical. This study aims to assess the effectiveness of machine-learning algorithms in predicting melanoma recurrence using clinical and histopathologic features from Electronic Health Records (EHRs). We collected 1720 early-stage melanomas: 1172 from the Mass General Brigham healthcare system (MGB) and 548 from the Dana-Farber Cancer Institute (DFCI). We extracted 36 clinicopathologic features and used them to predict the recurrence risk with supervised machine-learning algorithms. Models were evaluated internally and externally: (1) five-fold cross-validation of the MGB cohort; (2) the MGB cohort for training and the DFCI cohort for testing independently. In the internal and external validations, respectively, we achieved a recurrence classification performance of AUC: 0.845 and 0.812, and a time-to-event prediction performance of time-dependent AUC: 0.853 and 0.820. Breslow tumor thickness and mitotic rate were identified as the most predictive features. Our results suggest that machine-learning algorithms can extract predictive signals from clinicopathologic features for early-stage melanoma recurrence prediction, which will enable the identification of patients that may benefit from adjuvant immunotherapy.

Ulceration vs Mitosis in Cutaneous Melanoma: which is Superior for Predicting Prognosis Across Clinical Stages?

Ulceration and high mitosis are considered among the major unfavorable prognostic factors in the survival of cutaneous melanoma patients. The aim of this study was to investigate the clinical significance of these parameters and to compare them to see which one is superior to predicting prognosis across all clinical stages of melanoma. A total of 1,074 melanomas were analyzed retrospectively. Tumor ulceration was found to be limited to the local stage for predicting survival, whereas, mitosis maintained its prognostic strength for predicting survival across all clinical stages. Furthermore, no survival differences were observed between ulceration and mitosis across clinical stages.