Influence of sex on survival rates of HPV-positive oropharyngeal cancers.

The role of human papillomavirus (HPV) status for the prognosis of oropharyngeal cancers (OPCs) is discussed controversially. Here, we present an analysis of 144,969 head and neck cancer cases (ICD-10 codes: C00-C13) with a sub-cohort of 62,775 tumor cases of the oropharynx (C01, C09, and C10). To this end, de-identified data from electronic health records of about 60 healthcare organizations from 30 different countries were used. Odds ratios, hazard ratios (HRs), and Kaplan-Meier analyses were used to compare outcomes between different cancer entities of neoplasms of the base of the tongue (C01), of tonsils (C09), and of the oropharynx (C10) of women and men with and without HPV infection. To avoid the bias from different age distributions, the cohorts were balanced using propensity score matching. The 5-year survival rate for HPV-positive patients is somewhat better than that for HPV-negative patients, but for age- and sex-balanced cohorts, there remains no significant advantage for HPV-positive patients [HR, 1.126 (0.897-1.413)]. Looking at the different entities and HPV status for age-matched male and female patients separately, HPV is a significantly positive prognostic factor for female patients in some entities, whereas for male patients, it is only a positive prognostic factor for malignant neoplasms of oropharynx (C10) [HR, 1.077 (0.602-1.926)].

Man vs. machine: comparison of pharmacogenetic expert counselling with a clinical medication support system in a study with 200 genotyped patients.

BACKGROUND: Medication problems such as strong side effects or inefficacy occur frequently. At our university hospital, a consultation group of specialists takes care of patients suffering from medication problems. Nevertheless, the counselling of poly-treated patients is complex, as it requires the consideration of a large network of interactions between drugs and their targets, their metabolizing enzymes, and their transporters, etc. PURPOSE: This study aims to check whether a score-based decision-support system (1) reduces the time and effort and (2) suggests solutions at the same quality level. PATIENTS AND METHODS: A total of 200 multimorbid, poly-treated patients with medication problems were included. All patients were considered twice: manually, as clinically established, and using the Drug-PIN decision-support system. Besides diagnoses, lab data (kidney, liver), phenotype (age, gender, BMI, habits), and genotype (genetic variants with actionable clinical evidence I or IIa) were considered, to eliminate potentially inappropriate medications and to select individually favourable drugs from existing medication classes. The algorithm is connected to automatically updated knowledge resources to provide reproducible up-to-date decision support. RESULTS: The average turnaround time for manual poly-therapy counselling per patient ranges from 3 to 6 working hours, while it can be reduced to ten minutes using Drug-PIN. At the same time, the results of the novel computerized approach coincide with the manual approach at a level of > 90%. The holistic medication score can be used to find favourable drugs within a class of drugs and also to judge the severity of medication problems, to identify critical cases early and automatically. CONCLUSION: With the computerized version of this approach, it became possible to score all combinations of all alternative drugs from each class of drugs administered ("personalized medication landscape ") and to identify critical patients even before problems are reported ("medication alert"). Careful comparison of manual and score-based results shows that the incomplete manual consideration of genetic specialties and pharmacokinetic conflicts is responsible for most of the (minor) deviations between the two approaches. The meaning of the reduction of working time for experts by about 2 orders of magnitude should not be underestimated, as it enables practical application of personalized medicine in clinical routine.

Individualized Drugs' Selection by Evaluation of Drug Properties, Pharmacogenomics and Clinical Parameters: Performance of a Bioinformatic Tool Compared to a Clinically Established Counselling Process.

PURPOSE: Inefficacy and safety concerns are main medications' problems, especially in the case of poly-therapies, when drug-drug interactions may alter the expected drug disposition. Ongoing efforts are aimed to establish drug selection processes aimed to preemptive evaluation of a plethora of factors affecting patient's specific drug response, including pharmacogenomic markers, in order to minimize prescription of improper medications. In previous years, we established at the University Hospital Sant'Andrea of Rome, Italy, a Precision Medicine Service based on a multi-disciplinary experts' team. The team is in charge to produce a drug therapy counselling report, including pharmacogenomic, pharmacokinetic and pharmacodynamic considerations. In this study, we aimed to evaluate the performance of this established "manual" process of therapy selection with a novel bioinformatic tool, the Drug-PIN system. PATIENTS AND METHODS: A total of 200 patients diagnosed with Major Depressive Disorders or a depressive episode in Bipolar Disorder, with at least three previous failed treatments, who underwent pharmacogenomic profiling and therapy counselling in the Sant'Andrea Hospital from 2017 to 2020. The baseline poly-therapy of these patients was re-evaluated and optimized by Drug-PIN. Results of the Drug-PIN poly-therapy evaluation/optimization were compared with the results of the original poly-therapy evaluation/optimization by therapy counselling. To compare the results between the two processes, the risk associated with each poly-therapy was classified as low, moderate, or high. RESULTS: The number of baseline poly-therapies classified in low-, moderate- or high-risk did not change significantly between manual system or Drug-PIN system. As the counselling process, also the Drug-PIN system produces a significant decrease in the predicted treatment-associated risk. CONCLUSION: Drug-PIN substantially replicates the output of the counselling process, allowing a substantial reduction in the time needed for therapy evaluation. Availability of an effective bioinformatic tool for proper drug selection is expected to exponentially increase the actuation of targeted therapy strategies.