Integrating additional factors into the TNM staging for cutaneous melanoma by machine learning.

BACKGROUND: Integrating additional factors into the TNM staging system is needed for more accurate risk classification and survival prediction for patients with cutaneous melanoma. In the present study, we introduce machine learning as a novel tool that incorporates additional prognostic factors to improve the current TNM staging system. METHODS AND FINDINGS: Cancer-specific survival data for cutaneous melanoma with at least a 5 years follow-up were extracted from the Surveillance, Epidemiology, and End Results Program of the National Cancer Institute and split into the training set (40,781 cases) and validation set (5,390 cases). Five factors were studied: the primary tumor (T), regional lymph nodes (N), distant metastasis (M), age (A), and sex (S). The Ensemble Algorithm for Clustering Cancer Data (EACCD) was applied to the training set to generate prognostic groups. Utilizing only T, N, and M, a basic prognostic system was built where patients were stratified into 10 prognostic groups with well-separated survival curves, similar to 10 AJCC stages. These 10 groups had a significantly higher accuracy in survival prediction than 10 stages (C-index = 0.7682 vs 0.7643; increase in C-index = 0.0039, 95% CI = (0.0032, 0.0047); p-value = 7.2×10-23). Nevertheless, a positive association remained between the EACCD grouping and the AJCC staging (Spearman's rank correlation coefficient = 0.8316; p-value = 4.5×10-13). With additional information from A and S, a more advanced prognostic system was established using the training data that stratified patients into 10 groups and further improved the prediction accuracy (C-index = 0.7865 vs 0.7643; increase in C-index = 0.0222, 95% CI = (0.0191, 0.0254); p-value = 8.8×10-43). Both internal validation using the training set and temporal validation using the validation set showed good stratification and a high predictive accuracy of the prognostic systems. CONCLUSIONS: The EACCD allows additional factors to be integrated into the TNM to create a prognostic system that improves patient stratification and survival prediction for cutaneous melanoma. This integration separates favorable from unfavorable clinical outcomes for patients and improves both cohort selection for clinical trials and treatment management.

Intralesional Cidofovir for Treatment of Acyclovir-Resistant Laryngeal Herpes Manifesting as Supraglottic Mass.

INTRODUCTION:: Laryngopharyngeal herpes simplex virus infection is rare and presents typically in the supraglottis. Findings on presentation can range from small mucosal lesions to fungating obstructive masses mimicking neoplasm. Laryngopharyngeal herpes is a medically treated disease. OBJECTIVES:: Identify potential treatment in cases that are refractory to antiviral medications. METHODS:: Individual case with treatment adapted from other case report. CASE PRESENTATION:: We report a case of bulky, obstructive supraglottic and glottic herpes virus laryngitis that presented with dysphonia, dysphagia, and airway complaints resistant to acyclovir analogues that was treated effectively with intralesional cidofovir injection. CONCLUSIONS:: Our promising initial response suggests a potential novel treatment for this unusual condition.

Creating Prognostic Systems for Well-Differentiated Thyroid Cancer Using Machine Learning.

Updates to staging models are needed to reflect a greater understanding of tumor behavior and clinical outcomes for well-differentiated thyroid carcinomas. We used a machine learning algorithm and disease-specific survival data of differentiated thyroid carcinoma from the Surveillance, Epidemiology, and End Results Program of the National Cancer Institute to integrate clinical factors to improve prognostic accuracy. The concordance statistic (C-index) was used to cut dendrograms resulting from the learning process to generate prognostic groups. We created one computational prognostic model (7 prognostic groups with C-index = 0.8583) based on tumor size (T), regional lymph nodes (N), status of distant metastasis (M), and age to mirror the contemporary American Joint Committee on Cancer (AJCC) staging system (C-index = 0.8387). We showed that adding histologic type (papillary and follicular) improved the survival prediction of the model. We also showed that 55 is the best cutoff of age in the model, consistent with the changes from the most recent 8th edition staging manual from AJCC. The demonstrated approach has the potential to create prognostic systems permitting data driven and real time analysis that can aid decision-making in patient management and prognostication.

Barriers to pediatric cochlear implantation: A parental survey.

OBJECTIVE: This study aims to (1) determine barriers in the pediatric cochlear implantation process specific to publicly insured patients, wherein delayed implantation has been reported, and (2) compare the perceived barriers between publicly and privately insured patients. SETTING: Tertiary care cochlear implantation center at academic pediatric hospital. STUDY DESIGN: Cross-sectional survey, retrospective chart review. METHODS: The validated, 39 item Barriers to Care Questionnaire was administered to the parents of 80 recipients of cochlear implantation by two surgeons between 2013 and 2016. Survey results and diagnosis to implant interval were compared based on public or private insurance status. Two-tailed Mann-Whitney and Fisher's exact test was used for statistical analysis. RESULTS: Of 110 cochlear implants, 27 of 80 (34%) English-speaking parents completed the survey. 15 were privately insured and 12 were publicly insured. 23 of 27 respondents received cochlear implantation for pre-lingual sensorineural hearing loss. Publicly insured patients had significantly longer median time from diagnosis to implant than privately insured (19 vs. 8 mo, p = 0.01). The three worst scoring barrier categories for privately insured families in order were Pragmatics, Expectations, and Marginalization, whereas for publicly insured families it was Pragmatics, Skills, and Expectations. The worst scoring question for privately insured patients was "Having to take time off work". For the publicly insured, it was "Lack of communication." CONCLUSION: Privately insured patients reported more barriers on the Barriers to Care Questionnaire than publicly insured patients did. Although pragmatics was the worst-scoring barrier category for both groups, difficulties found on the survey ranked differently for each group. This information can help providers address disparities and access barriers for vulnerable patients.

Creating prognostic systems for cancer patients: A demonstration using breast cancer.

Integrating additional prognostic factors into the tumor, lymph node, metastasis staging system improves the relative stratification of cancer patients and enhances the accuracy in planning their treatment options and predicting clinical outcomes. We describe a novel approach to build prognostic systems for cancer patients that can admit any number of prognostic factors. In the approach, an unsupervised learning algorithm was used to create dendrograms and the C-index was used to cut dendrograms to generate prognostic groups. Breast cancer data from the Surveillance, Epidemiology, and End Results Program of the National Cancer Institute were used for demonstration. Two relative prognostic systems were created for breast cancer. One system (7 prognostic groups with C-index = 0.7295) was based on tumor size, regional lymph nodes, and no distant metastasis. The other system (7 prognostic groups with C-index = 0.7458) was based on tumor size, regional lymph nodes, no distant metastasis, grade, estrogen receptor, progesterone receptor, and age. The dendrograms showed a relationship between survival and prognostic factors. The proposed approach is able to create prognostic systems that have a good accuracy in survival prediction and provide a manageable number of prognostic groups. The prognostic systems have the potential to permit a thorough database analysis of all information relevant to decision-making in patient management and prognosis.

Heat Release Property and Fire Performance of the Nomex/Cotton Blend Fabric Treated with a Nonformaldehyde Organophosphorus System.

Blending Nomex® with cotton improves its affordability and serviceability. Because cotton is a highly flammable fiber, Nomex®/cotton blend fabrics containing more than 20% cotton require flame-retardant treatment. In this research, combination of a hydroxyl functional organophosphorus oligmer (HFPO) and 1,2,3,4-butanetetracarboxylic acid (BTCA) was used for flame retardant finishing of the 65/35 Nomex®/cotton blend woven fabric. The system contains HFPO as a flame retardant, BTCA as a bonding agent, and triethenolamine (TEA) as a reactive additive used to enhance the performance of HFPO/BTCA. Addition of TEA improves the hydrolysis resistance of the HFPO/BTCA crosslinked polymeric network on the blend fabric. Additionally, TEA enhances HFPO's flame retardant performance by reducing formation of calcium salts and also by providing synergistic nitrogen to the treated blend fabric. The Nomex®/cotton blend fabric treated with the HFPO/BTCA/TEA system shows high flame resistance and high laundering durability at a relatively low HFPO concentration of 8% (w/w). The heat release properties of the treated Nomex®/cotton blend fabric were measured using microscale combustion calorimetry. The functions of BTCA; HFPO and TEA on the Nomex®/cotton blend fabric were elucidated based on the heat release properties, char formation, and fire performance of the treated blend fabric.

Nonformaldehyde durable press finishing of cotton fabrics using the combination of maleic acid and sodium hypophosphite.

Polycarboxylic acids have been used as nonformaldehyde crosslinking agents for cotton with sodium hypophosphite (NaH2PO2) as the catalyst to replace the formaldehyde-based dimethyloldihydroxyethleneurea (DMDHEU). Maleic acid (MA), an α, ß-unsaturated bifunctional carboxylic acid, can esterify cotton but is not able to form crosslinking between two cellulose molecules by itself. In this research, we discovered that the wrinkle resistance of the cotton fabric treated with MA and NaH2PO2 was significantly increased and phosphorus was bound to cotton when the treated fabric was exposed to temperatures higher than that required for esterification of cotton by MA. Elevation of the fabric wrinkle resistance and increase in quantity of the phosphorus bound to cotton had similar dependency on curing temperature, on MA concentration, and on NaH2PO2 concentration. All the data support the hypothesis that H-P-(residual of NaH2PO2) added to >CC< of the MA already bound to cotton by esterification, thus forming a new crosslink between two cotton cellulose molecules. The cotton fabrics treated by MA/NaH2PO2 showed fabric wrinkle resistance similar to that treated with DMDHEU, but the breaking strength and tearing strength of the MA-treated cotton fabrics were significantly improved.