Development and validation of a machine learning-based predictive model to improve the prediction of inguinal status of anal cancer patients: A preliminary report

Introduction: The role of prophylactic inguinal irradiation (PII) in the treatment of anal cancer patients is controversial. We developped an innovative algorithm based on the Machine Learning (ML) allowing the tailoring of the prescription of PII. Results: Once verified on the independent testing set, J48 showed the better performances, with specificity, sensitivity, and accuracy rates in predicting relapsing patients of 86.4%, 50.0% and 83.1% respectively (vs 36.5%, 90.4% and 80.25%, respectively, for LR). Methods: We classified 194 anal cancer patients with Logistic Regression (LR) and other 3 ML techniques based on decision trees (J48, Random Tree and Random Forest), using a large set of clinical and therapeutic variables. We tested obtained ML algorithms on an independent testing set of 65 anal cancer patients. TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis) methodology was used for the development, the Quality Assurance and the description of the experimental procedures. Conclusion: In an internationally approved quality assurance framework, ML seems promising in predicting the outcome of patients that would benefit or not of the PII. Once confirmed in larger and/or multi-centric databases, ML could support the physician in tailoring the treatment and in deciding if deliver or not the PII

Role of brachytherapy in the treatment of cancers of the anal canal: Long-term follow-up and multivariate analysis of a large monocentric retrospective series

Background and purpose: There are few data on long-term clinical results and tolerance of brachytherapy in anal canal cancer. We present one of the largest retrospective analyses of anal canal cancers treated with external beam radiotherapy with/without (±) chemotherapy followed by a brachytherapy boost. Materials and methods: We performed a retrospective analysis of clinical results in terms of efficacy and toxicity. The impact of different clinical and therapeutic variables on these outcomes was studied. Results: From May 1992 to December 2009, 209 patients received brachytherapy after external beam radiotherapy ± chemotherapy. Of these patients, 163 were stage II or stage IIIA (UICC 2002) and 58 were N1-3. According to age, ECOG performance status (PS), and comorbidities, patients received either radiotherapy alone (58/209) or radiochemotherapy (151/209). The median follow-up was 72.8months. The 5- and 10-year local control rates were 78.6 and 73.9 %, respectively. Globally, severe acute and late G3-4 reactions (NCI-CTC scale v. 4.0) occurred in 11.2 and 6.3 % of patients, respectively. Univariate analysis showed the statistical impact of the pelvic treatment volume (p = 0.046) and of the total dose (p = 0.02) on the risk of severe acute and late toxicities, respectively. Only six patients required permanent colostomy because of severe late anorectal toxicities. Conclusion: After a long follow-up time, brachytherapy showed an acceptable toxicity profile and high local control rates in patients with anal canal cancer

pMineR: An Innovative R Library for Performing Process Mining in Medicine

Process Mining is an emerging discipline investigating tasks related with the automated identification of process models, given realworld data (Process Discovery). The analysis of such models can provide useful insights to domain experts. In addition, models of processes can be used to test if a given process complies (Conformance Checking) with specifications. For these capabilities, Process Mining is gaining importance and attention in healthcare. In this paper we introduce pMineR, an R library specifically designed for performing Process Mining in the medical domain, and supporting human experts by presenting processes in a human-readable way

Role of fluorine-18 fluorodeoxyglucose PET/CT in head and neck oncology: the point of view of the radiation oncologist

Squamous cell carcinoma is the most common malignant tumour of the head and neck. The initial TNM staging, the evaluation of the tumour response during treatment, and the long-term surveillance are crucial moments in the approach to head and neck squamous cell carcinoma (HNSCC). Thus, at each of these moments, the choice of the best diagnostic tool providing the more precise and larger information is crucial. Positron emission tomography with fluorine-18 fludeoxyglucose integrated with CT (F-18-FDG-PET/CT) rapidly gained clinical acceptance, and it has become an important imaging tool in routine clinical oncology. However, controversial data are currently available, for example, on the role of F-18-FDG-PET/CT imaging during radiotherapy planning, the prognostic value or its real clinical impact on treatment decisions. In this article, the role of F-18-FDG-PET/CT imaging in HNSCC during pre-treatment staging, radiotherapy planning, treatment response assessment, prognosis and follow-up is reviewed focusing on current evidence and controversial issues. A proposal on how to integrate F-18-FDG-PET/CT in daily clinical practice is also described

The Prognostic Role of Baseline Eosinophils in HPV-Related Cancers: a Multi-institutional Analysis of Anal SCC and OPC Patients Treated with Radical CT-RT

Background and Aim Anal squamous cell carcinoma (SCC) and oropharyngeal cancer (OPC) are rare tumors associated with HPV infection. Bioumoral predictors of response to chemoradiation (CT-RT) are lacking in these settings. With the aim to find new biomarkers, we investigated the role of eosinophils in both HPV-positive anal SCC and HPV-related oropharyngeal cancer (OPC). Methods We retrieved clinical and laboratory data of patients with HPV-positive anal SCC treated with CT-RT in 5 institutions, and patients with locally advanced OPC SCC treated with CT-RT in 2 institutions. We examined the association between baseline eosinophil count (the best cutoff has been evaluated by ROC curve analysis: 100 x 109/L) and disease-free survival (DFS). Unadjusted and adjusted hazard ratios by baseline characteristics were calculated using the Cox proportional hazards model. Results Three hundred four patients with HPV-positive anal SCCs and 168 patients with OPCs (122 HPV-positive, 46 HPV-negative diseases) were analyzed. In anal SCC, low eosinophil count (9/L) correlates to a better DFS (HR = 0.59; p = 0.0392); likewise, in HPV-positive OPC, low eosinophil count correlates to a better DFS (HR = 0.50; p = 0.0428). In HPV-negative OPC, low eosinophil count confers worse DFS compared to high eosinophil count (HR = 3.53; p = 0.0098). After adjustment for age and sex, eosinophils were confirmed to be independent prognostic factors for DFS (HR = 4.55; p = 0.0139). Conclusion Eosinophil count could be used as a prognostic factor in anal HPV-positive SCC. The worse prognosis showed in HPV-positive patients with high eosinophil count is likely to derive from an unfavorable interaction between the HPV-induced immunomodulation and eosinophils, which may hamper the curative effect of RT

What Role Can Process Mining Play in Recurrent Clinical Guidelines Issues? A Position Paper

[EN] In the age of Evidence-Based Medicine, Clinical Guidelines (CGs) are recognized to be an indispensable tool to support physicians in their daily clinical practice. Medical Informatics is expected to play a relevant role in facilitating diffusion and adoption of CGs. However, the past pioneering approaches, often fragmented in many disciplines, did not lead to solutions that are actually exploited in hospitals. Process Mining for Healthcare (PM4HC) is an emerging discipline gaining the interest of healthcare experts, and seems able to deal with many important issues in representing CGs. In this position paper, we briefly describe the story and the state-of-the-art of CGs, and the efforts and results of the past approaches of medical informatics. Then, we describe PM4HC, and we answer questions like how can PM4HC cope with this challenge? 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Developing clinical practice guidelines: types of evidence and outcomes; values and economics, synthesis, grading, and presentation and deriving recommendations. Implementation Science, 7(1). doi:10.1186/1748-5908-7-61Legido-Quigley, H., Panteli, D., Brusamento, S., Knai, C., Saliba, V., Turk, E., … Busse, R. (2012). Clinical guidelines in the European Union: Mapping the regulatory basis, development, quality control, implementation and evaluation across member states. Health Policy, 107(2-3), 146-156. doi:10.1016/j.healthpol.2012.08.004Rashidian, A., Eccles, M. P., & Russell, I. (2008). Falling on stony ground? A qualitative study of implementation of clinical guidelines’ prescribing recommendations in primary care. Health Policy, 85(2), 148-161. doi:10.1016/j.healthpol.2007.07.011Yang, W.-S., & Hwang, S.-Y. (2006). A process-mining framework for the detection of healthcare fraud and abuse. 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Journal of the American Medical Informatics Association, 18(6), 738-748. doi:10.1136/amiajnl-2010-000033Quaglini, S., Stefanelli, M., Cavallini, A., Micieli, G., Fassino, C., & Mossa, C. (2000). Guideline-based careflow systems. Artificial Intelligence in Medicine, 20(1), 5-22. doi:10.1016/s0933-3657(00)00050-6Schadow, G., Russler, D. C., & McDonald, C. J. (2001). Conceptual alignment of electronic health record data with guideline and workflow knowledge. International Journal of Medical Informatics, 64(2-3), 259-274. doi:10.1016/s1386-5056(01)00196-4González-Ferrer, A., ten Teije, A., Fdez-Olivares, J., & Milian, K. (2013). Automated generation of patient-tailored electronic care pathways by translating computer-interpretable guidelines into hierarchical task networks. Artificial Intelligence in Medicine, 57(2), 91-109. doi:10.1016/j.artmed.2012.08.008Shabo, A., Parimbelli, E., Quaglini, S., Napolitano, C., & Peleg, M. (2016). Interplay between Clinical Guidelines and Organizational Workflow Systems. Methods of Information in Medicine, 55(06), 488-494. doi:10.3414/me16-01-0006Mulyar, N., van der Aalst, W. M. P., & Peleg, M. (2007). A Pattern-based Analysis of Clinical Computer-interpretable Guideline Modeling Languages. Journal of the American Medical Informatics Association, 14(6), 781-787. doi:10.1197/jamia.m2389Grando, M. A., Glasspool, D., & Fox, J. (2012). A formal approach to the analysis of clinical computer-interpretable guideline modeling languages. Artificial Intelligence in Medicine, 54(1), 1-13. doi:10.1016/j.artmed.2011.07.001Kaiser, K., & Marcos, M. (2015). Leveraging workflow control patterns in the domain of clinical practice guidelines. BMC Medical Informatics and Decision Making, 16(1). doi:10.1186/s12911-016-0253-zMartínez-Salvador, B., & Marcos, M. (2016). Supporting the Refinement of Clinical Process Models to Computer-Interpretable Guideline Models. Business & Information Systems Engineering, 58(5), 355-366. doi:10.1007/s12599-016-0443-3Decision Model and Notation Version 1.0https://www.omg.org/spec/DMN/1.0Ghasemi, M., & Amyot, D. (2016). Process mining in healthcare: a systematised literature review. International Journal of Electronic Healthcare, 9(1), 60. doi:10.1504/ijeh.2016.078745Rebuge, Á., & Ferreira, D. R. (2012). Business process analysis in healthcare environments: A methodology based on process mining. Information Systems, 37(2), 99-116. doi:10.1016/j.is.2011.01.003Rovani, M., Maggi, F. M., de Leoni, M., & van der Aalst, W. M. P. (2015). Declarative process mining in healthcare. Expert Systems with Applications, 42(23), 9236-9251. doi:10.1016/j.eswa.2015.07.040Rojas, E., Munoz-Gama, J., Sepúlveda, M., & Capurro, D. (2016). Process mining in healthcare: A literature review. 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Immune inflammation indicators in anal cancer patients treated with concurrent chemoradiation: training and validation cohort with online calculator (ARC: Anal Cancer Response Classifier)

Background: In anal cancer, there are no markers nor other laboratory indexes that can predict prognosis and guide clinical practice for patients treated with concurrent chemoradiation. In this study, we retrospectively investigated the influence of immune inflammation indicators on treatment outcome of anal cancer patients undergoing concurrent chemoradiotherapy. Methods: All patients had a histologically proven diagnosis of squamous cell carcinoma of the anal canal/margin treated with chemoradiotherapy according to the Nigro's regimen. Impact on prognosis of pre-treatment systemic index of inflammation (SII) (platelet x neutrophil/lymphocyte), neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) were analyzed. Results: A total of 161 consecutive patients were available for the analysis. Response to treatment was the single most important factor for progression-free survival (PFS) and overall survival (OS). At univariate analysis, higher SII level was significantly correlated to lower PFS (p<0.01) and OS (p=0.046). NLR level was significantly correlated to PFS (p=0.05), but not to OS (p=0.06). PLR level significantly affected both PFS (p<0.01) and OS (p=0.02). On multivariate analysis pre-treatment, SII level was significantly correlated to PFS (p=0.0079), but not to OS (p=0.15). We developed and externally validated on a cohort of 147 patients a logistic nomogram using SII, nodal status and pre-treatment Hb levels. Results showed a good predictive ability with C-index of 0.74. An online available calculator has also been developed. Conclusion: The low cost and easy profile in terms of determination and reproducibility make SII a promising tool for prognostic assessment in this oncological setting

COVID-19 vaccinations: summary guidance for Cancer patients in 28Languages: breaking barriers to Cancer patient Information

Background: Covid-19 vaccination has started in the majority of the countries at the global level. Cancer patients are at high risk for infection, serious illness, and death from COVID-19 and need vaccination guidance and support. Guidance availability in the English language only is a major limit for recommendations' delivery and their application in the world's population and generates information inequalities across the different populations. Methods: Most of the available COVID-19 vaccination guidance for cancer patients was screened and scrutinized by the European Cancer Patients Coalition (ECPC) and an international oncology panel of 52 physicians from 33 countries. Results: A summary guidance was developed and provided in 28 languages in order to reach more than 70 percent of the global population. Conclusion: Language barrier and e-guidance availability in the native language are the most important barriers when communicating with patients. E-guidance availability in various native languages should be considered a major priority by international medical and health organizations that are communicating with patients at the global level.info:eu-repo/semantics/publishedVersio