Mohs micrographic surgery (MMS) is considered the gold standard for difficult‐to‐treat malignant skin tumors, whose incidence is on the rise. Currently, there are no agreed upon classifiers to predict complex MMS procedures. Such classifiers could enable better patient scheduling, reduce staff burnout and improve patient education. Our goal was to create an accessible and interpretable classifier(s) that would predict complex MMS procedures. A retrospective study applying machine learning models to a dataset of 8644 MMS procedures to predict complex wound reconstruction and number of MMS procedure stages. Each procedure record contained preoperative data on patient demographics, estimated clinical tumor size prior to surgery (mean diameter), tumor characteristics and tumor location, and postoperative procedure outcomes included the wound reconstruction technique and the number of MMS stages performed in order to achieve tumor‐free margins. For the number of stages complexity classification model, the area under the receiver operating characteristic curve (AUROC) was 0.79 (good performance), with model accuracy of 77%, sensitivity of 71%, specificity of 77%, positive prediction value (PPV) of 14% and negative prediction value (NPV) of 98%. The results for the wound reconstruction complexity classification model were 0.84 for the AUROC (excellent performance), with model accuracy of 75%, sensitivity of 72%, specificity of 76%, PPV of 39% and NPV of 93%. The ML models we created predict the complexity of the components that comprise the MMS procedure. Using the accessible and interpretable tool we provide online, clinicians can improve the management and well‐being of their patients. Study limitation is that models are based on data generated from a single surgeon.
Clinical misclassification between cutaneous squamous cell carcinoma (cSCC) and basal cell carcinoma (BCC) affects treatment plans and carries risks of potential for recurrence, metastases morbidity and mortality. We report the development of a novel tissue sampling approach with molecular biopsy using electroporation. The methods, coined e-biopsy, enables non-thermal permeabilization of cells in the skin for efficient vacuum-assistant extraction of informative biomolecules for rapid diagnosis. We used e-biopsy for ex vivo proteome extraction from 3 locations per patient in 21 cSCC and 21 BCC pathologically validated human tissue samples. The total 126 extracted proteomes were profiled using LC/MS/MS. The obtained mass spectra presented significantly different proteome profiles for cSCC and BCC with several hundreds of proteins significantly differentially expressed in each tumor in comparison to the other. Notably, 17 proteins were uniquely expressed in BCC and 7 were uniquely expressed in cSCC patients. Statistical analysis of differentially expressed proteins found 31 cellular processes, 23 cellular functions and 10 cellular components significantly different between cSCC and BCC. Machine Learning classification models constructed on the sampled proteomes enabled the separation of cSCC patients from BCC with average cross-validation accuracy of 81%, cSCC prediction positive predictive value (PPV) of 78.7% and sensitivity of 92.3%, which is comparable to initial diagnostics in a clinical setup. Finally, the protein-protein interaction analysis of the 11 most informative proteins, derived from Machine Learning framework, enabled detection of a novel protein-protein interaction network valuable for further understanding of skin tumors. Our results provide evidence that the e-biopsy approach could potentially be used as a tool to support cutaneous tumors classification with rapid molecular profiling.
DM is highly integrated into the daily medical practices of plastic surgeons in Israel.
BACKGROUND Mohs micrographic surgery (MMS) is a widely used technique for removal of cutaneous tumors. The procedure is well-tolerated with little surgical or postoperative pain. OBJECTIVE This study examined pain levels after Mohs surgery throughout the first week of recovery and the relation to patient demographics, lesion characteristics, surgery details, and postoperative analgesia. METHODS A 2-year prospective observational study included patients who underwent MMS. Patients rated the severity of postoperative pain once daily until removal of sutures and documented analgesics used. Analyses of patient and lesion characteristics along with reconstruction methods were conducted. RESULTS A total of 2,178 patients were included in the study. Pain levels were strongest on the first postoperative day (POD) and were significantly different between genders on POD 3. Site of skin lesion, method of reconstruction, and number of stages of MMS were significantly related to postoperative pain levels on univariate and multivariate analyses. Postoperative consumption of analgesics differed significantly between men and women and was not correlated to age. CONCLUSION Mohs surgery is generally nonpainful and is well-tolerated by men and women across all ages. The site of the lesion and method of reconstruction are the major determinants affecting the perception of pain.M ohs micrographic surgery (MMS), first described by F. Mohs in 1938, 1 is a widely used and accepted technique for complete removal of cutaneous tumors under local anesthesia. 2 The use of MMS has increased steadily, and it is estimated that 1 in 4 malignant skin tumors is treated using this technique. 3 The procedure is continued until margins are free of malignant cells and may last even longer depending on the necessary reconstruction; therefore, it is crucial to ensure long-lasting analgesia.In most cases, MMS involves only cutaneous layers and as such is believed to be well-tolerated without much surgical or postoperative pain. Several studies suggest that postoperative pain after nondermatologic surgeries is affected by anxiety. [4][5][6] Relations between pain levels after MMS and patient's gender, as well as tumor size and analgesic consumption have been reported previously. [7][8][9][10] This study examined pain levels after MMS throughout the first week of recovery and their relation to patient demographics, lesion characteristics, surgery details, and postoperative analgesia.
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