Recognizing and preventing unacknowledged prescribing errors associated with polypharmacy.

BACKGROUND: Prescribing errors put an enormous burden on health and the economy, claiming implementation of effective methods to prevent/reduce them. Polypharmacy regimens (five or more drugs) are highly prone to unacknowledged prescribing errors, since the complex network of drug-drug interactions, guidelines and contraindications is challenging to be adequately evaluated in the prescription phase, especially if different doctors are involved. Clinical decision support systems aimed at polypharmacy evaluation may be crucial to recognize and correct prescribing errors. METHODS: A commercial clinical decision support system (Drug-PIN®) was applied to estimate the frequency of unrecognized prescribing errors in a group of 307 consecutive patients accessing the hospital pre-admission service of the Sant'Andrea Hospital of Rome, Italy, in the period April-June 2023. Drug-PIN® is a two-step system, first scoring the risk (low, moderate or high) associated with a certain therapy-patient pair, then allowing therapy optimization by medications exchanges. We defined prescribing errors as cases where therapy optimization could achieve consistent reduction of the Drug-PIN® calculated risk. RESULTS: Polypharmacy was present in 205 patients, and moderate to high risk for medication harm was predicted by Drug-PIN® in 91 patients (29.6%). In 58 of them (63.7%), Drug-PIN® guided optimization of the therapy could be achieved, with a statistically significant reduction of the calculated therapy-associated risk score. Patients whose therapy cannot be improved have a statistically significant higher number of used drugs. Considering the overall study population, the rate of avoidable prescribing errors was 18.89%. CONCLUSIONS: Results suggest that computer-aided evaluation of medication-associated harm could be a valuable and actionable tool to identify and prevent prescribing errors in polypharmacy. We conducted the study in a Hospital pre-admission setting, which is not representative of the general population but represents a hotspot to intercept fragile population, where a consistent fraction of potentially harmful polypharmacy regimens could be promptly identified and corrected by systematic use of adequate clinical decision support tools.

An exploration into CTEPH medications: Combining natural language processing, embedding learning, in vitro models, and real-world evidence for drug repurposing.

BACKGROUND: In the modern era, the growth of scientific literature presents a daunting challenge for researchers to keep informed of advancements across multiple disciplines. OBJECTIVE: We apply natural language processing (NLP) and embedding learning concepts to design PubDigest, a tool that combs PubMed literature, aiming to pinpoint potential drugs that could be repurposed. METHODS: Using NLP, especially term associations through word embeddings, we explored unrecognized relationships between drugs and diseases. To illustrate the utility of PubDigest, we focused on chronic thromboembolic pulmonary hypertension (CTEPH), a rare disease with an overall limited number of scientific publications. RESULTS: Our literature analysis identified key clinical features linked to CTEPH by applying term frequency-inverse document frequency (TF-IDF) scoring, a technique measuring a term's significance in a text corpus. This allowed us to map related diseases. One standout was venous thrombosis (VT), which showed strong semantic links with CTEPH. Looking deeper, we discovered potential repurposing candidates for CTEPH through large-scale neural network-based contextualization of literature and predictive modeling on both the CTEPH and the VT literature corpora to find novel, yet unrecognized associations between the two diseases. Alongside the anti-thrombotic agent caplacizumab, benzofuran derivatives were an intriguing find. In particular, the benzofuran derivative amiodarone displayed potential anti-thrombotic properties in the literature. Our in vitro tests confirmed amiodarone's ability to reduce platelet aggregation significantly by 68% (p = 0.02). However, real-world clinical data indicated that CTEPH patients receiving amiodarone treatment faced a significant 15.9% higher mortality risk (p<0.001). CONCLUSIONS: While NLP offers an innovative approach to interpreting scientific literature, especially for drug repurposing, it is crucial to combine it with complementary methods like in vitro testing and real-world evidence. Our exploration with benzofuran derivatives and CTEPH underscores this point. Thus, blending NLP with hands-on experiments and real-world clinical data can pave the way for faster and safer drug repurposing approaches, especially for rare diseases like CTEPH.

Semaphorin heterodimerization in cis regulates membrane targeting and neocortical wiring.

Disruption of neocortical circuitry and architecture in humans causes numerous neurodevelopmental disorders. Neocortical cytoarchitecture is orchestrated by various transcription factors such as Satb2 that control target genes during strict time windows. In humans, mutations of SATB2 cause SATB2 Associated Syndrome (SAS), a multisymptomatic syndrome involving epilepsy, intellectual disability, speech delay, and craniofacial defects. Here we show that Satb2 controls neuronal migration and callosal axonal outgrowth during murine neocortical development by inducing the expression of the GPI-anchored protein, Semaphorin 7A (Sema7A). We find that Sema7A exerts this biological activity by heterodimerizing in cis with the transmembrane semaphorin, Sema4D. We could also observe that heterodimerization with Sema7A promotes targeting of Sema4D to the plasma membrane in vitro. Finally, we report an epilepsy-associated de novo mutation in Sema4D (Q497P) that inhibits normal glycosylation and plasma membrane localization of Sema4D-associated complexes. These results suggest that neuronal use of semaphorins during neocortical development is heteromeric, and a greater signaling complexity exists than was previously thought.

Clinical impact of drug-drug interactions on abemaciclib in the real-world experience of AB-ITALY study.

Abemaciclib demonstrated clinical benefit in women affected by HR+/HER2- advanced breast cancer (aBC). Drug-drug interactions (DDIs) can lead to reduced treatment efficacy or increased toxicity. This retro-prospective study aimed to evaluate outcomes, DDIs' impact, and toxicities of abemaciclib combined with endocrine therapy in a real-world setting. Patients from 12 referral Italian hospitals with HR+/HER2- aBC who received abemaciclib were included. Clinical data about comorbidities, concurrent medications, outcomes, and adverse events (AE) were collected. Drug-PIN® (Personalized Interactions Network) is a tool recognizing the role of multiple interactions between active and/or pro-drug forms combined with biochemical and demographic patient data. The software was used to define the Drug-PIN score and Drug-PIN tier (green, yellow, dark yellow, and red) for each patient. Univariate and multivariate analyses were performed to identify predictors of patients' PFS or toxicity. One hundred seventy-three patients were included. 13% of patients had >75years. The overall response rate (ORR) was 63%. The general population's median PFS (mPFS) was 22 months (mo), while mOS were not reached. Patients treated with abemaciclib in combination with AI and fulvestrant had a mPFS of 36 and 19 mo, respectively. The most common toxicities were diarrhea, asthenia, and neutropenia detected in 63%,49%, and 49% of patients. The number of concomitant medications and comorbidities were not associated with survival outcomes (22 vs 17 mo, p = 0.068, p = 0.99). Drug-PIN tier from dark yellow to red and Drug-PIN score >12 were associated with shorter PFS compared to no/low-risk DDIs and score <12 (15 vs 23, p = 0.005, p = 0.0017). Drug interaction was confirmed as an independent biomarker in a multivariate model (p = 0.02). No difference in any grade AE, severe toxicities, and diarrhea were detected among different age subgroups. No association was found between Drug-PIN score or Drug-PIN tier and overall toxicity (p = 0.44), severe AEs (p = 0.11), or drug reduction (p = 0.27). The efficacy and safety of abemaciclib plus ET were confirmed in a real-world setting, even in the elderly population and patients with comorbidities. Evaluation of DDIs with Drug-PIN appears to be an independent predictor of PFS.

Rosacea is strongly associated with melanoma in Caucasians.

Rosacea is often considered a cosmetic problem but is known to be associated with a variety of comorbidities. To identify such risks, we generated two age- and sex-matched real-world cohorts of 122,444 patients each with and without rosacea. In contrast to earlier studies, we found significant associations with malignant melanoma (OR 6.02, 95% CI 5.76-6.32). This association does not exist for an Asian sub-cohort, which could explain previous inconclusive or conflicting reports. Several strongly associated comorbidities like visual disturbances (ICD-10: H53-H54; OR 4.80, 4.68-4.92), metabolic disorders (E73-E79; OR 3.17, 3.11-3.22), joint problems (M25; OR 4.16, 4.08-4.25) and type 2 diabetes (E11; OR 1.62, 1.58-1.65) should be watched as a risk for rosacea patients. Rosacea is associated with some comorbidities and ethnicity may be a risk factor in melanoma development. The retrospective nature of this study and the sole use of ICD-10 code based filtering calls for future validation of our findings. Additionally, confounding factors such as skin type and previous UV exposure should be included in future studies.

ProTox 3.0: a webserver for the prediction of toxicity of chemicals.

Interaction with chemicals, present in drugs, food, environments, and consumer goods, is an integral part of our everyday life. However, depending on the amount and duration, such interactions can also result in adverse effects. With the increase in computational methods, the in silico methods can offer significant benefits to both regulatory needs and requirements for risk assessments and the pharmaceutical industry to assess the safety profile of a chemical. Here, we present ProTox 3.0, which incorporates molecular similarity and machine-learning models for the prediction of 61 toxicity endpoints such as acute toxicity, organ toxicity, clinical toxicity, molecular-initiating events (MOE), adverse outcomes (Tox21) pathways, several other toxicological endpoints and toxicity off-targets. All the ProTox 3.0 models are validated on independent external sets and have shown strong performance. ProTox envisages itself as a complete, freely available computational platform for in silico toxicity prediction for toxicologists, regulatory agencies, computational chemists, and medicinal chemists. The ProTox 3.0 webserver is free and open to all users, and there is no login requirement and can be accessed via https://tox.charite.de. The web server takes a 2D chemical structure as input and reports the toxicological profile of the compound for each endpoint with a confidence score and overall toxicity radar plot and network plot.

Non-animal models for blood-brain barrier permeability evaluation of drug-like compounds.

Diseases related to the central nervous system (CNS) are major health concerns and have serious social and economic impacts. Developing new drugs for CNS-related disorders presents a major challenge as it actively involves delivering drugs into the CNS. Therefore, it is imperative to develop in silico methodologies to reliably identify potential lead compounds that can penetrate the blood-brain barrier (BBB) and help to thoroughly understand the role of different physicochemical properties fundamental to the BBB permeation of molecules. In this study, we have analysed the chemical space of the CNS drugs and compared it to the non-CNS-approved drugs. Additionally, we have collected a feature selection dataset from Muehlbacher et al. (J Comput Aided Mol Des 25(12):1095-1106, 2011. 10.1007/s10822-011-9478-1) and an in-house dataset. This information was utilised to design a molecular fingerprint that was used to train machine learning (ML) models. The best-performing models reported in this study achieved accuracies of 0.997 and 0.98, sensitivities of 1.0 and 0.992, specificities of 0.971 and 0.962, MCCs of 0.984 and 0.958, and ROC-AUCs of 0.997 and 0.999 on an imbalanced and a balanced dataset, respectively. They demonstrated overall good accuracies and sensitivities in the blind validation dataset. The reported models can be applied for fast and early screening drug-like molecules with BBB potential. Furthermore, the bbbPythoN package can be used by the research community to both produce the BBB-specific molecular fingerprints and employ the models mentioned earlier for BBB-permeability prediction.

Association of Herpes simplex infection with significantly increased risk of head and neck cancer: real-world evidence of about 500,000 patients.

BACKGROUND: The role of viral agents in the development of head and neck cancers has remained controversial. While markers of viral origin have been isolated from oral cancer tissues, a causative relationship has yet to be shown. The aim of this study was to evaluate the relationship between head and neck cancers and Herpes simplex virus, one of the most common viral infections of the oral orifice. METHODS: Here, we conducted a retrospective analysis of two age- and gender-matched cohorts extracted from the real-world database TriNetX on March 10th, 2023, each consisting of 249,272 patients with and without Herpes simplex infections (ICD-10: B00). The diagnoses C00-C14 were analyzed, and risk analysis and Kaplan-Meier survival statics were computed. RESULTS: The strongest association was found for lip cancer (ICD-10: C00) with a hazard ratio [HR (CI 95% low-high)] of 3.08 (1.77-5.35). A significant association with HR of 1.17 (1.02-1.34) was found for the entire group of head and neck cancers. Confounders like smoking and alcohol dependence were considered using propensity score matching. CONCLUSION: The surprisingly strong correlation with lip, oral cavity, and pharynx neoplasms sheds new light on supposedly harmless herpes simplex infections, suggesting them as a possible new factor for risk stratification.

Exogenous Estrogen in the Development of Head and Neck Cancer.

Importance: Sex differences in head and neck cancer (HNC) incidence suggest a potential contribution of sex hormones. Objective: To assess the role of exogenous estrogen exposure in the development of HNC in female patients. Design, Settings, and Participants: This large multicenter cohort study using clinical records from the TriNetX real-world database included 20 years of data (through May 31, 2023) from 87 health care organizations. The TriNetX database was searched for medical records for female patients with and without exogenous estrogen exposure according to their chronological age. Cohort 1 included 731 366 female patients aged 18 to 45 years old with regular oral contraceptive (OC) intake and cohort 2 included 3 886 568 patients in the same age group who did not use OC. Cohort 3 comprised 135 875 female patients at least 50 years old receiving hormone replacement therapy (HRT), whereas cohort 4 included 5 875 270 patients at least 50 years old without HRT. Propensity score matching was performed for the confounders age, alcohol dependence, and nicotine dependence. Data analyses were performed in May 2023. Main Outcome and Measures: Diagnosis of HNC (International Statistical Classification of Diseases and Related Health Problems, Tenth Revision: C00-C14), and after propensity score matching (1:1 nearest-neighbor greedy matching), a risk analysis to investigate risk differences and risk ratios (RRs) with a 95% CI. Results: Among the 718 101 female patients in each of cohorts 1 and 2 (mean [SD] age at diagnosis, 25.9 [6.7] years), those with OC intake had a higher risk of an HNC diagnosis (RR, 1.47; 95% CI, 1.21-1.78) than those without OC use. Among the 131 835 female patients in each of cohorts 3 and 4 (mean [SD] age, 67.9 [12.0] years), those with postmenopausal HRT intake had a lower risk of an HNC diagnosis (RR, 0.77; 95% CI, 0.64-0.92) than those without HRT use. Conclusions and Relevance: The findings of this cohort study illustrate a positive association between OC and a negative association between HRT and the development of HNC in female patients. Given the limitations of the TriNetX database, future research should include detailed information on the intake of OC and HRT and reproductive health information (eg, age at menarche/menopause, number of pregnancies) to more accurately define the strength and direction of the possible association between exogeneous estrogen exposure and the development of HNC in female patients.

Beneficial Effect of Metformin on the Five-Year Survival in about 40,000 Patients with Head and Neck Cancer.

INTRODUCTION: Even in times of new therapy regimes, the overall survival of patients with head and neck cancer remains low. Since the previous studies showed the beneficial effect of metformin medication on the survival of patients with cancer, our objective was to investigate if-and in which way-metformin medication affects the overall survival of patients with head and neck cancer. METHODS: Clinical data pertaining to patients diagnosed with head and neck cancer (International Classification of Diseases 10 codes C00-C14, C31, and C32) were retrospectively retrieved from the TriNetX network (TriNetX, Cambridge, MA, USA). The initial cohort extracted from the network was stratified into two groups: patients on metformin medication (cohort I), and individuals not on metformin medication (cohort II). The matching criteria included age, gender, BMI, type 2 diabetes, and risk factors, such as nicotine and alcohol abuse/dependence. Kaplan-Meier analysis, risk analysis, and the calculation of odds and hazard ratios were conducted. Additionally, the Hemoglobin A1c values were subject to analysis. RESULTS: Following matching, each cohort comprised 20,416 patients. Cohort I exhibited a higher five-year survival rate at 75.3%, in contrast to cohort II, which registered a rate of 69.8%. The odds ratio was 0.79 (95% CI = 0.75-0.83), and the hazard ratio was 0.78 (95% CI = 0.75-0.82). CONCLUSION: Metformin medication may correlate with improved five-year survival rates in patients with head and neck cancer. Since potentially influencing factors such as comorbidities and the initial tumor stage were not available, the results of our retrospectively conducted study must be interpreted with caution.

Withdrawn 2.0-update on withdrawn drugs with pharmacovigilance data.

One challenge in the development of novel drugs is their interaction with potential off-targets, which can cause unintended side-effects, that can lead to the subsequent withdrawal of approved drugs. At the same time, these off-targets may also present a chance for the repositioning of withdrawn drugs for new indications, which are potentially rare or more severe than the original indication and where certain adverse reactions may be avoidable or tolerable. To enable further insights into this topic, we updated our database Withdrawn by adding pharmacovigilance data from the FDA Adverse Event Reporting System (FAERS), as well as mechanism of action and human disease pathway prediction features for drugs that are or were temporarily withdrawn or discontinued in at least one country. As withdrawal data are still spread over dozens of national websites, we are continuously updating our lists of discontinued or withdrawn drugs and related (off-)targets. Furthermore, new systematic entry points for browsing the data, such as an ATC tree, were added, increasing the accessibility of the database in a user-friendly way. Withdrawn 2.0 is publicly available without the need for registration or login at https://bioinformatics.charite.de/withdrawn_3/index.php.

The risk of osteomyelitis after mandibular fracture is doubled in men versus women: analysis of 300,000 patients.

Postoperative complications following mandibular fracture treatment vary from local wound infections to severe conditions including osteomyelitis and impaired fracture healing. Several risk factors have been associated with the development healing disorders, including fracture localisation, treatment modality and substance abuse. However, limited research on the sex-specific influence of these complications exists. A total of about 300,000 female and male patients with mandibular fractures were examined in two cohorts. After matching for confounders (age, nicotine and alcohol dependence, malnutrition, overweight, anaemia, diabetes, osteoporosis and vitamin D deficiency), two cohorts were compared with propensity-score-matched patients according to outcomes (osteomyelitis, pseudoarthrosis and disruption of the wound) within 1 year after fracture. There were significant differences between female and male patients regarding the occurrence of osteomyelitis (odds ratio [OR] [95% confidence interval]: 0.621 [0.563; 0.686]) and disruption of the wound (OR [95% confidence interval]: 0.703 [0.632; 0.782]). Surprisingly, matching for the expected confounders did not change the results substantially. Sex plays a dominant role in determining the risk stratification for postoperative osteomyelitis and disruption of the wound, after accounting for other potential confounding factors. Additional research is needed to understand the underlying mechanisms and to develop sex-specific strategies to prevent these complications.

Worse prognosis in females with new onset of depression after oral cancer diagnosis: a retrospective case-control study.

Background: Sex-related discrepancies in the prognosis of oral cancer patients have not been clarified. This study aimed to assess survival outcomes and potential prognostic factors in female and male patients with oral cancer. Methods: A retrospective search of the TriNetX network (TriNetX, Cambridge, Massachusetts, USA) was conducted to identify patients diagnosed with oral cancer (International Classification of Diseases (ICD)-10 codes C02-C06), within the past 20 years from the access date April 21, 2023. Patients were categorized according to sex (female vs. male). Following matching for age and risk factors such as nicotine dependence and alcohol abuse, Kaplan-Meier analysis was performed and risk, odds, and hazard ratios were calculated. Outcome variables were five-year disease-free survival (DFS) and overall survival (OS). Additionally, the female and male patient cohort were compared with regard to the novel diagnosis of depression (depressive episode, major depressive disorder, dysthymic disorder) after the tumor diagnosis. Results: A total of 77,348 patients were assessed. After propensity score matching, 26,578 male and 26,578 female patients were included in each group (mean age 63 years). DFS (71.92% in females vs. 68.29% in males; hazard ratio (HR) 0.870; p < 0.001) and OS (77.08% in females vs. 71.74% in males; HR 0.793; p < 0.001) were significantly higher in the female cohort. However, in patients diagnosed with depression after the initial cancer diagnosis (N = 4,824), survival was worse in female patients compared to male patients (82.48% in females vs. 86.10% in males; HR 1.341; p < 0.001). Conclusion: This retrospective case-control study showed that females with oral cancer had a better DFS and OS than males. However, survival in females with a newly diagnosed depression after the oral cancer diagnosis was worse compared to those of male oral cancer patients. Depression may be a relevant prognostic factor that contributes to sex disparities in oral cancer patients.

The Impact of Drug-Drug Interactions on the Toxicity Profile of Combined Treatment with BRAF and MEK Inhibitors in Patients with BRAF-Mutated Metastatic Melanoma.

BACKGROUND: BRAF and MEK inhibition is a successful strategy in managing BRAF-mutant melanoma, even if the treatment-related toxicity is substantial. We analyzed the role of drug-drug interactions (DDI) on the toxicity profile of anti-BRAF/anti-MEK therapy. METHODS: In this multicenter, observational, and retrospective study, DDIs were assessed using Drug-PIN software (V 2/23). The association between the Drug-PIN continuous score or the Drug-PIN traffic light and the occurrence of treatment-related toxicities and oncological outcomes was evaluated. RESULTS: In total, 177 patients with advanced BRAF-mutated melanoma undergoing BRAF/MEK targeted therapy were included. All grade toxicity was registered in 79% of patients. Cardiovascular toxicities occurred in 31 patients (17.5%). Further, 94 (55.9%) patients had comorbidities requiring specific pharmacological treatments. The median Drug-PIN score significantly increased when the target combination was added to the patient's home therapy (p-value < 0.0001). Cardiovascular toxicity was significantly associated with the Drug-PIN score (p-value = 0.048). The Drug-PIN traffic light (p = 0.00821) and the Drug-PIN score (p = 0.0291) were seen to be significant predictors of cardiotoxicity. Patients with low-grade vs. high-grade interactions showed a better prognosis regarding overall survival (OS) (p = 0.0045) and progression-free survival (PFS) (p = 0.012). The survival analysis of the subgroup of patients with cardiological toxicity demonstrated that patients with low-grade vs. high-grade DDIs had better outcomes in terms of OS (p = 0.0012) and a trend toward significance in PFS (p = 0.068). CONCLUSIONS: DDIs emerged as a critical issue for the risk of treatment-related cardiovascular toxicity. Our findings support the utility of DDI assessment in melanoma patients treated with BRAF/MEK inhibitors.

Comparison of the risk of hospital admission, need for ventilation, sepsis, pneumonitis and death among the recent monkeypox outbreak and historical outbreaks.

BACKGROUND: The course of monkeypox can be severe. Our aim was to retrospectively compare the risk of hospital admission, the need for ventilation, sepsis, pneumonitis and death between the recent outbreak and historical outbreaks. MATERIALS AND METHODS: Cases of monkeypox were retrieved from the TriNetX database and assigned to either cohort I (recent outbreak between May 1st and September 16th, 2022) and cohort II (historical outbreaks before May 1st, 2022). After matching for age distribution, statistical analysis was performed. RESULTS: Of 640 patients with monkeypox 81 subjects per cohort remained after matching (mean age±standard deviation = 36.1±18.3 years). Within 56 days after diagnosis 10 patients per cohort were hospitalized (12.4%) and/or developed sepsis (12.4%). The risk of ventilation and pneumonitis were significantly lower among cohort I compared with cohort II (0 vs. 10 cases; risk difference = 12.4%; p = 0.001; Log-Rank test). No cases of death were recorded. CONCLUSION: Even though monkeypox provides a risk of severe courses, the infection is self-limiting in most cases. Unlike past outbreaks, the risk of ventilation and pneumonitis may be relatively low among recent outbreaks.

Machine Learning and Pharmacogenomics at the Time of Precision Psychiatry.

Traditional medicine and biomedical sciences are reaching a turning point because of the constantly growing impact and volume of Big Data. Machine Learning (ML) techniques and related algorithms play a central role as diagnostic, prognostic, and decision-making tools in this field. Another promising area becoming part of everyday clinical practice is personalized therapy and pharmacogenomics. Applying ML to pharmacogenomics opens new frontiers to tailored therapeutical strategies to help clinicians choose drugs with the best response and fewer side effects, operating with genetic information and combining it with the clinical profile. This systematic review aims to draw up the state-of-the-art ML applied to pharmacogenomics in psychiatry. Our research yielded fourteen papers; most were published in the last three years. The sample comprises 9,180 patients diagnosed with mood disorders, psychoses, or autism spectrum disorders. Prediction of drug response and prediction of side effects are the most frequently considered domains with the supervised ML technique, which first requires training and then testing. The random forest is the most used algorithm; it comprises several decision trees, reduces the training set's overfitting, and makes precise predictions. ML proved effective and reliable, especially when genetic and biodemographic information were integrated into the algorithm. Even though ML and pharmacogenomics are not part of everyday clinical practice yet, they will gain a unique role in the next future in improving personalized treatments in psychiatry.

DRD2, DRD3, and HTR2A Single-Nucleotide Polymorphisms Involvement in High Treatment Resistance to Atypical Antipsychotic Drugs.

BACKGROUND: The objective of this study was to investigate the DRD2 rs1800497, rs1799732, rs1801028, DRD3 rs6280, and HTR2A rs6314, rs7997012, and rs6311 single-nucleotide polymorphism (SNP) correlations with resistance to second-generation antipsychotics (SGAs) in a real-world sample of patients with treatment-resistant mental disorders. METHODS: We divided 129 participants into a high treatment resistance (HTR) group (current treatment with two SGAs, or clozapine, or classic neuroleptics for a failure of previous SGAs trials) and a low treatment resistance (LTR) group (current treatment with one atypical antipsychotic). We used Next-Generation Sequencing on DNA isolated from peripheral blood samples to analyze the polymorphisms. We performed logistic regression to search for predictors of HTR membership. RESULTS: A diagnosis of schizophrenia significantly predicted the HTR membership compared to other diagnoses. Other predictors were the DRD3 rs6280 C|T (OR = 22.195) and T|T (OR = 18.47) vs. C|C, HTR2A rs7997012 A|G vs. A|A (OR = 6.859) and vs. G|G (OR = 2.879), and DRD2 rs1799732 I|I vs. D|I (OR = 12.079) genotypes. CONCLUSIONS: A diagnosis of schizophrenia and the DRD2 rs1799732, DRD3 rs6280, and HTR2A rs7997012 genotypes can predict high treatment resistance to SGAs.

Using real-world evidence data and digital monitoring to analyze the hepatotoxic profiles of biologics across more than two million patients.

The real-world evidence data from multiple sources which includes information on patient health status and medical behavior in routine clinical setup can give deeper insights into drugs 'safety and efficacy. The RWE-based analysis in this study revealed a statistically significant link between biologics usage and hepatotoxicity in patients. To the best of our knowledge, this study is the first to conduct a large-scale multi-cohort analysis on the hepatotoxic profiles of biologics. Biologics are among the most prescribed medicines for several chronic inflammatory diseases. These agents target critical pathogenic pathways, but they may also have serious side effects. It is important to analyze whether biologics agents are an added concern or therapeutic opportunity. Real-world evidence (RWE) data were extracted for patients using biologics to monitor the safety and effectiveness of the biologics. All six biologics included in this analysis-are mostly highly prescribed biologics. The aim of the study was to assess the hepatotoxic profiles of subjects using different biologics. We evaluated the safety of current treatment regimens for patients in a large real-world cohort from multiple health care centers. Total number of eligible patients retrieved from the database is 38,112,285. Of these 38 million patients, 2.3 million take biologics. The primary objective was to assess the potential adverse hepatotoxic effects of the six biologics; adalimumab, trastuzumab, prevnar13, pegfilgrastim, interferon-beta1a and insulin glargine across different indications like diabetes mellitus, encounter for immunization, malignant neoplasm of breast, multiple sclerosis, malignant neoplasm of kidney, aplastic anaemias, radiation sickness, Crohn's disease, psoriasis, rheumatoid arthritis, spondylopathies. Data from patients using the six most-used biologics-adalimumab, trastuzumab, prevnar13, pegfilgrastim, interferon-beta1a and insulin glargine were retrieved from a global research network covering 250 million patients' data from 19 countries, and assigned to the cohorts 1 and 2, respectively. The cohorts were propensity score matched for age and sex. After defining the primary outcome as "hepatotoxicity" (endpoint defined as ICD-10 code: K71 (hepatotoxic liver disease), a Kaplan-Meier survival analysis was performed, and risk ratios (RR), odds ratios (OR), and hazard ratios (HR) were determined. A total number of 2,312,655 subjects were eligible who take biologics, and after matching total cohorts accounted for 2,303,445. We have considered the clinical data as a 1:1 matched-study design, using propensity score-matched sub-cohorts to better control for confounding associations that might stem from different distributions of age and gender between the whole dataset and the subset of patients. We discovered evidence supporting the hepatotoxic-causing effect of biologic drugs: (i) all biologics considered together had an OR of 1.9 (95% CI, 1.67-2.35), with (ii) Adalimumab 1.9 (95% CI, 1.72-2.20), Trastuzumab 1.7 (95% CI, 1.2-2.3), Prevnar13 2.3 (95% CI, 2.16-2.60), Pegfilgrastim 2.3 (95% CI, 2.0-2.50), Interferon-Beta1a 1.7 (95% CI, 1.18-2.51), and Insulin glargine 1.9 (95% CI, 1.8-1.99). Our findings indicate that clinicians should consider evaluating hepatic profiles of patients undergoing treatment with biologic drugs and counsel them regarding the risk of developing hepatic injury. Strengths of the study includes a large sample size and robust statistical techniques. Limitations of this study include lack of detailed information regarding clinical severity. Major biologics are associated with hepatotoxicity. We discovered evidence supporting the hepatotoxicity-causing effects of biologics: all biologics considered together had an OR of 1.9 (95% CI, 1.67-2.35).

Statin Medication Improves Five-Year Survival Rates in Patients with Head and Neck Cancer: A Retrospective Case-Control Study of about 100,000 Patients.

INTRODUCTION: The overall survival among head and neck cancer patients is still low, even in a time of new therapy regimes. Regarding cancer patients' survival, statin use has already proven to be associated with favorable survival outcomes. Our objective was to investigate the influence of statin medication on the overall survival of head and neck cancer patients. METHODS: Retrospective clinical data of patients diagnosed with head and neck cancer (International Classification of Diseases codes: C00-C14) were retrieved from a real-world evidence database. The initial cohort was divided into patients with statin medication, who were assigned to building cohort I, and subjects without statin medication, who were assigned to cohort II, both matched by age, gender, and risk factors (nicotine and alcohol abuse/dependence). Subsequently, Kaplan-Meier and risk analyses were performed, and odds and hazard ratios were calculated. RESULTS: After matching, each cohort contained 48,626 patients (cohort I = females: 15,409; (31.7%), males 33,212 (68.3%); mean age ± standard deviation (SD) at diagnosis 66.3 ± 11.4 years; cohort II = females: 15,432; (31.7%), males 33,187 (68.2%); mean age ± standard deviation (SD) at diagnosis 66.4 ± 11.5 years). Five-year survival was found to be significantly higher for cohort I, with 75.19%, respectively 70.48% for cohort II. These findings were correlated significantly with a risk of death of 15.9% (cohort I) and 17.2% (cohort II); the odds ratio was 0.91 (95% CI: 0.881-0.942) and the hazard ratio 0.80 (0.777-0.827). CONCLUSIONS: The results indicate that the five-year survival of head and neck cancer patients is significantly improved by statin medication. As this study was conducted retrospectively, our data must be interpreted with caution, especially since other potential influencing factors and the initial tumor stage were not available.