Taipei Medical University Clinical Research Database: a collaborative hospital EHR database aligned with international common data standards

OBJECTIVE

The objective of this paper is to provide a comprehensive overview of the development and features of the Taipei Medical University Clinical Research Database (TMUCRD), a repository of real-world data (RWD) derived from electronic health records (EHRs) and other sources.

METHODS

TMUCRD was developed by integrating EHRs from three affiliated hospitals, including Taipei Medical University Hospital, Wan-Fang Hospital and Shuang-Ho Hospital. The data cover over 15 years and include diverse patient care information. The database was converted to the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) for standardisation.

RESULTS

TMUCRD comprises 89 tables (eg, 29 tables for each hospital and 2 linked tables), including demographics, diagnoses, medications, procedures and measurements, among others. It encompasses data from more than 4.15 million patients with various medical records, spanning from the year 2004 to 2021. The dataset offers insights into disease prevalence, medication usage, laboratory tests and patient characteristics.

DISCUSSION

TMUCRD stands out due to its unique advantages, including diverse data types, comprehensive patient information, linked mortality and cancer registry data, regular updates and a swift application process. Its compatibility with the OMOP CDM enhances its usability and interoperability.

CONCLUSION

TMUCRD serves as a valuable resource for researchers and scholars interested in leveraging RWD for clinical research. Its availability and integration of diverse healthcare data contribute to a collaborative and data-driven approach to advancing medical knowledge and practice.

Machine-Learning Based Risk Assessment for Cancer Therapy-Related Cardiac Adverse Events Among Breast Cancer Patients

The study aims to develop machine-learning models to predict cardiac adverse events in female breast cancer patients who receive adjuvant therapy. We selected breast cancer patients from a retrospective dataset of the Taipei Medical University Clinical Research Database and Taiwan Cancer Registry between January 2004 and December 2020. Patients were monitored at the date of prescribed chemo- and/or -target therapies until cardiac adverse events occurred during a year. Variables were used, including demographics, comorbidities, medications, and lab values. Logistics regression (LR) and artificial neural network (ANN) were used. The performance of the algorithms was measured by the area under the receiver operating characteristic curve (AUC). In total, 1321 patients (an equal 15039 visits) were included. The best performance of the artificial neural network (ANN) model was achieved with the AUC, precision, recall, and F1-score of 0.89, 0.14, 0.82, and 0.2, respectively. The most important features were a pre-existing cardiac disease, tumor size, estrogen receptor (ER), human epidermal growth factor receptor 2 (HER2), cancer stage, and age at index date. Further research is necessary to determine the feasibility of applying the algorithm in the clinical setting and explore whether this tool could improve care and outcomes.

Unveiling the future of COVID-19 patient care: groundbreaking prediction models for severe outcomes or mortality in hospitalized cases

Background

Previous studies have identified COVID-19 risk factors, such as age and chronic health conditions, linked to severe outcomes and mortality. However, accurately predicting severe illness in COVID-19 patients remains challenging, lacking precise methods.

Objective

This study aimed to leverage clinical real-world data and multiple machine-learning algorithms to formulate innovative predictive models for assessing the risk of severe outcomes or mortality in hospitalized patients with COVID-19.

Methods

Data were obtained from the Taipei Medical University Clinical Research Database (TMUCRD) including electronic health records from three Taiwanese hospitals in Taiwan. This study included patients admitted to the hospitals who received an initial diagnosis of COVID-19 between January 1, 2021, and May 31, 2022. The primary outcome was defined as the composite of severe infection, including ventilator use, intubation, ICU admission, and mortality. Secondary outcomes consisted of individual indicators. The dataset encompassed demographic data, health status, COVID-19 specifics, comorbidities, medications, and laboratory results. Two modes (full mode and simplified mode) are used; the former includes all features, and the latter only includes the 30 most important features selected based on the algorithm used by the best model in full mode. Seven machine learning was employed algorithms the performance of the models was evaluated using metrics such as the area under the receiver operating characteristic curve (AUROC), accuracy, sensitivity, and specificity.

Results

The study encompassed 22,192 eligible in-patients diagnosed with COVID-19. In the full mode, the model using the light gradient boosting machine algorithm achieved the highest AUROC value (0.939), with an accuracy of 85.5%, a sensitivity of 0.897, and a specificity of 0.853. Age, vaccination status, neutrophil count, sodium levels, and platelet count were significant features. In the simplified mode, the extreme gradient boosting algorithm yielded an AUROC of 0.935, an accuracy of 89.9%, a sensitivity of 0.843, and a specificity of 0.902.

Conclusion

This study illustrates the feasibility of constructing precise predictive models for severe outcomes or mortality in COVID-19 patients by leveraging significant predictors and advanced machine learning. These findings can aid healthcare practitioners in proactively predicting and monitoring severe outcomes or mortality among hospitalized COVID-19 patients, improving treatment and resource allocation.

Near infrared imaging system for preventing blood vision obstruction in endoscopy

Spinal endoscopy procedure is commonly used in the diagnosis and treatment of various health problems and is effective. Bleeding is one of the most common complications of spinal endoscopy procedures. Blood vision obstruction (BVO), that is, obstruction of the endoscopic camera lens caused by the accumulation of blood in the surgical field, is a serious problem in endoscopic procedures. This study presents what we believe to be a new approach to addressing BVO with external multispectral imaging. The study was completed using a BVO simulation model, and the results reveal that this technology can be used to effectively overcome BVO and provide clear images of the anatomy, enabling more effective diagnosis and treatment. This technique may enable improvement of the outcomes of endoscopic procedures and could have far-reaching implications in the field of endoscopy.

A novel prediction model of the risk of pancreatic cancer among diabetes patients using multiple clinical data and machine learning

INTRODUCTION

Pancreatic cancer is associated with poor prognosis. Considering the increased global incidence of diabetes cases and that individuals with diabetes are considered a high-risk subpopulation for pancreatic cancer, it is critical to detect the risk of pancreatic cancer within populations of person living = with diabetes. This study aimed to develop a novel prediction model for pancreatic cancer risk among patients with diabetes, using = a real-world database containing clinical features and employing numerous artificial intelligent approach algorithms.

METHODS

This retrospective observational study analyzed data on patients with Type 2 diabetes from a multisite Taiwanese EMR database between 2009 and 2019. Predictors were selected in accordance with the literature review and clinical perspectives. The prediction models were constructed using machine learning algorithms such as logistic regression, linear discriminant analysis, gradient boosting machine, and random forest.

RESULTS

The cohort consisted of 66,384 patients. The Linear Discriminant Analysis (LDA) model generated the highest AUROC of 0.9073, followed by the Voting Ensemble and Gradient Boosting machine models. LDA, the best model, exhibited an accuracy of 84.03%, a sensitivity of 0.8611, and a specificity of 0.8403. The most significant predictors identified for pancreatic cancer risk were glucose, glycated hemoglobin, hyperlipidemia comorbidity, antidiabetic drug use, and lipid-modifying drug use.

CONCLUSION

This study successfully developed a highly accurate 4-year risk model for pancreatic cancer in patients with diabetes using real-world clinical data and multiple machine-learning algorithms. Potentially, our predictors offer an opportunity to identify pancreatic cancer early and thus increase prevention and invention windows to impact survival in diabetic patients.

Machine learning approaches for predicting 5-year breast cancer survival: A multicenter study

The study used clinical data to develop a prediction model for breast cancer survival. Breast cancer prognostic factors were explored using machine learning techniques. We conducted a retrospective study using data from the Taipei Medical University Clinical Research Database, which contains electronic medical records from three affiliated hospitals in Taiwan. The study included female patients aged over 20 years who were diagnosed with primary breast cancer and had medical records in hospitals between January 1, 2009 and December 31, 2020. The data were divided into training and external testing datasets. Nine different machine learning algorithms were applied to develop the models. The performances of the algorithms were measured using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and F1-score. A total of 3914 patients were included in the study. The highest AUC of 0.95 was observed with the artificial neural network model (accuracy, 0.90; sensitivity, 0.71; specificity, 0.73; PPV, 0.28; NPV, 0.94; and F1-score, 0.37). Other models showed relatively high AUC, ranging from 0.75 to 0.83. According to the optimal model results, cancer stage, tumor size, diagnosis age, surgery, and body mass index were the most critical factors for predicting breast cancer survival. The study successfully established accurate 5-year survival predictive models for breast cancer. Furthermore, the study found key factors that could affect breast cancer survival in Taiwanese women. Its results might be used as a reference for the clinical practice of breast cancer treatment.

Ranitidine Use and Incident Cancer in a Multinational Cohort

Importance

Ranitidine, the most widely used histamine-2 receptor antagonist (H2RA), was withdrawn because of N-nitrosodimethylamine impurity in 2020. Given the worldwide exposure to this drug, the potential risk of cancer development associated with the intake of known carcinogens is an important epidemiological concern.

Objective

To examine the comparative risk of cancer associated with the use of ranitidine vs other H2RAs.

Design, Setting, and Participants

This new-user active comparator international network cohort study was conducted using 3 health claims and 9 electronic health record databases from the US, the United Kingdom, Germany, Spain, France, South Korea, and Taiwan. Large-scale propensity score (PS) matching was used to minimize confounding of the observed covariates with negative control outcomes. Empirical calibration was performed to account for unobserved confounding. All databases were mapped to a common data model. Database-specific estimates were combined using random-effects meta-analysis. Participants included individuals aged at least 20 years with no history of cancer who used H2RAs for more than 30 days from January 1986 to December 2020, with a 1-year washout period. Data were analyzed from April to September 2021.

Exposure

The main exposure was use of ranitidine vs other H2RAs (famotidine, lafutidine, nizatidine, and roxatidine).

Main Outcomes and Measures

The primary outcome was incidence of any cancer, except nonmelanoma skin cancer. Secondary outcomes included all cancer except thyroid cancer, 16 cancer subtypes, and all-cause mortality.

Results

Among 1 183 999 individuals in 11 databases, 909 168 individuals (mean age, 56.1 years; 507 316 [55.8%] women) were identified as new users of ranitidine, and 274 831 individuals (mean age, 58.0 years; 145 935 [53.1%] women) were identified as new users of other H2RAs. Crude incidence rates of cancer were 14.30 events per 1000 person-years (PYs) in ranitidine users and 15.03 events per 1000 PYs among other H2RA users. After PS matching, cancer risk was similar in ranitidine compared with other H2RA users (incidence, 15.92 events per 1000 PYs vs 15.65 events per 1000 PYs; calibrated meta-analytic hazard ratio, 1.04; 95% CI, 0.97-1.12). No significant associations were found between ranitidine use and any secondary outcomes after calibration.

Conclusions and Relevance

In this cohort study, ranitidine use was not associated with an increased risk of cancer compared with the use of other H2RAs. Further research is needed on the long-term association of ranitidine with cancer development.

Prescription patterns of granulocyte colony-stimulating factors in patients with breast cancer: A real-world study

BACKGROUND AND OBJECTIVES

Myelosuppressive chemotherapy is effective for breast cancer but carries a potential risk of febrile neutropenia (FN). Clinical practice guidelines have recommended prophylaxis with granulocyte colony-stimulating factor (G-CSF) to reduce the incidence of FN in patients receiving chemotherapy. We aimed to examine the use of G-CSFs for primary prophylaxis for FN and to see whether it follows the guidelines. In addition, we examined the changes in the use of long-acting and short-acting G-CSFs in patients with breast cancer over the past ten years.

METHODS

This was a retrospective observational real-world study. The data were obtained from the clinical research database of three hospitals affiliated with Taipei Medical University. Patients with breast cancer who initiated their first chemotherapy regimen between January 1, 2011, and December 31, 2020, were identified by the ICD codes and their use of filgrastim or pegfilgrastim was identified by the Anatomical Therapeutic Chemical codes. Whether and how G-CSF was prescribed during the study patients' first chemotherapy regimen was examined, and the annual change in the total number of short- and long-acting G-CSFs prescribed to the study patients from 2011 to 2020 was analyzed.

RESULTS

Among the 2,444 patients who were prescribed at least one of the examined 15 breast cancer chemotherapy drugs, 1,414 did not use any G-CSFs during their first chemotherapy regimen while 145 used G-CSFs for primary prophylaxis and 185 for treatment. Among the patients receiving high FN risk regimens, only 8.6% used G-CSF for primary prophylaxis. The average (± SD) number of days for short-acting G-CSF use was 2.3 (± 1.5) days with a median of 2 days. In addition, it was found that there was a significant reduction in long-acting G-CSF use (p = 0.03) whereas the changes in short-acting G-CSF use over time were not significant (p = 0.50).

CONCLUSIONS

Our study results show that G-CSFs are used for primary prophylaxis in a small percentage of patients with breast cancer and the duration of short-acting G-CSF use is relatively short. Considering the significant clinical and economic impact of FN, it is hoped that the prescription patterns of G-CSFs observed can provide an important reference for future clinical practice and reimbursement policy.

Age and gender differences in misperceptions of body shape in a Taiwanese population

OBJECTIVES

Most studies of body size perception have been performed in adolescents, and most focus on gender differences in accurate perception of body size. This study investigated misperceptions of body sizes among males and females at different stages of adulthood in Taiwan.

DESIGNS

In-person home interviews were used to proportionally and randomly select 2095 adult men and women to answer the East Asian Social Survey. Participants were divided into 18-39, 40-64, and 65 + age groups. The main variables analyzed were self-perceived body size and standardized BMI.

RESULTS

Women, unlike men, were more likely to misperceive their body size as being overweight (OR = 2.92; p < .001). People with higher self-perceived social status were less likely to misperceive themselves as overweight (OR = 0.91; p = .01). People with college educations were 2.35 times more likely to overestimate their body size as being heavier than they were (p < .001) and less likely to underestimate it as being thinner than they were (OR = 0.45; p < .001). Women 18-35 and 36-64 years old were 6.96 and 4.31 times more likely (p < .001) to misperceive themselves as being overweight than women 65 or older, who were more likely to misperceive themselves as being too thin. There were no significant differences in body size misperceptions among the three age groups of adult men (p > .05). We found no different significant discrepancies between self-perceived body size and actual BMI between the older men and women (p = .16). However, younger and middle-aged men were 6.67 and 3.1 times more likely to misperceive themselves as being too thin than women in their same age groups (OR = 0.15 and OR = 0.32, respectively).

CONCLUSIONS

Age and gender affect self-perceptions of body size in Taiwan. Overall, women are more likely than men to misperceive themselves as being too big, and men are more likely than women to misperceive themselves as too thin. Older women, however, were more likely to misperceive themselves as being too thin. Clinicians and health educators should know that people's perceptions and concerns regarding their body size vary by age and gender.

Emotion recognition in doctor-patient interactions from real-world clinical video database: Initial development of artificial empathy

BACKGROUND AND OBJECTIVE

The promising use of artificial intelligence (AI) to emulate human empathy may help a physician engage with a more empathic doctor-patient relationship. This study demonstrates the application of artificial empathy based on facial emotion recognition to evaluate doctor-patient relationships in clinical practice.

METHODS

A prospective study used recorded video data of doctor-patient clinical encounters in dermatology outpatient clinics, Taipei Municipal Wanfang Hospital, and Taipei Medical University Hospital collected from March to December 2019. Two cameras recorded the facial expressions of four doctors and 348 adult patients during regular clinical practice. Facial emotion recognition was used to analyze the basic emotions of doctors and patients with a temporal resolution of 1 second. In addition, a physician-patient satisfaction questionnaire was administered after each clinical session, and two standard patients gave impartial feedback to avoid bias.

RESULTS

Data from 326 clinical session videos showed that (1) Doctors expressed more emotions than patients (t [326] > = 2.998, p < = 0.003), including anger, happiness, disgust, and sadness; the only emotion that patients showed more than doctors was surprise (t [326] = -4.428, p < .001) (p < .001). (2) Patients felt happier during the latter half of the session (t [326] = -2.860, p = .005), indicating a good doctor-patient relationship.

CONCLUSIONS

Artificial empathy can offer objective observations on how doctors' and patients' emotions change. With the ability to detect emotions in 3/4 view and profile images, artificial empathy could be an accessible evaluation tool to study doctor-patient relationships in practical clinical settings.

Comparison of local ablative therapies, including radiofrequency ablation, microwave ablation, stereotactic ablative radiotherapy, and particle radiotherapy, for inoperable hepatocellular carcinoma: a systematic review and meta-analysis

Surgical intervention is the first-line treatment in well-selected hepatocellular carcinoma (HCC) patients. However, only a few patients are suitable to receive radical surgery. We conducted a systematic review and meta-analysis to evaluate local control among four local ablative therapies in inoperable HCC patients, including radiofrequency ablation therapy (RFA), microwave ablation therapy (MWA), stereotactic ablative radiotherapy (SABR), and particle radiotherapy. The primary outcome was the local control rate and the secondary were regional and distant progression rates, overall survival rate, and adverse events. We included twenty-six studies from PubMed, EMBASE, and Cochrane Library databases. MWA (p < 0.001) and particle radiotherapy (p < 0.001) showed better performance of local control compared to RFA, while SABR (p = 0.276) showed a non-significant trend. However, SABR (p = 0.002) and particle radiotherapy (p < 0.001) showed better performance than RFA in HCCs of ≥ 30 mm in size. MWA showed a similar result to RFA while SABR and particle radiotherapy showed a lower survival rate in the 2-, 3-, and 4-year overall survival rates. Our results indicate that MWA, SABR and particle radiotherapy were safe and no inferior to RFA in local control rate. Besides, the local control rates of SABR and particle radiotherapy are better than RFA in HCC of ≥ 30 mm in size. As a result, we suggested that MWA, SABR and particle radiotherapy to be effective alternatives to RFA for inoperable HCC. Moreover, the tumor size should be taken into consideration for optimal treatment selection between local ablative therapies.

Association between Proton Pump Inhibitor Use and the Risk of Female Cancers: A Nested Case-Control Study of 23 Million Individuals

Background: Firm conclusions about whether long-term proton pump inhibitor (PPI) drug use impacts female cancer risk remain controversial. Objective: We aimed to investigate the associations between PPI use and female cancer risks. Methods: A nationwide population-based, nested case-control study was conducted within Taiwan’s Health and Welfare Data Science Center’s databases (2000−2016) and linked to pathologically confirmed cancer data from the Taiwan Cancer Registry (1979−2016). Individuals without any cancer diagnosis during the 17 years of the study served as controls. Case and control patients were matched 1:4 based on age, gender, and visit date. Conditional logistic regression with 95% confidence intervals (CIs) was applied to investigate the association between PPI exposure and female cancer risks by adjusting for potential confounders such as the Charlson comorbidity index and medication usage (metformin, aspirin, and statins). Results: A total of 233,173 female cancer cases were identified, consisting of 135,437 diagnosed with breast cancer, 64,382 with cervical cancer, 19,580 with endometrial cancer, and 13,774 with ovarian cancer. After matching each case with four controls, we included 932,692 control female patients. The number of controls for patients with breast cancer, cervical cancer, endometrial cancer, and ovarian cancer was 541,748, 257,528, 78,320, and 55,096, respectively. The use of PPIs was significantly associated with reduced risk of breast cancer and ovarian cancer in groups aged 20−39 years (adjusted odds ratio (aOR): 0.69, 95%CI: 0.56−0.84; p < 0.001 and aOR: 0.58, 95%CI: 0.34−0.99; p < 0.05, respectively) and 40−64 years (aOR: 0.89, 95%CI: 0.86−0.94; p < 0.0001 and aOR: 0.87, 95%CI: 0.75−0.99; p < 0.05, respectively). PPI exposure was associated with a significant decrease in cervical and endometrial cancer risks in the group aged 40−64 years (with aOR: 0.79, 95%CI: 0.73−0.86; p < 0.0001 and aOR: 0.72, 95%CI: 0.65−0.81; p < 0.0001, respectively). In contrast, in elderly women, PPI use was found to be insignificantly associated with female cancers among users. Conclusions: Our findings, based on real-world big data, can depict a comprehensive overview of PPI usage and female cancer risk. Further clinical studies are needed to elucidate the effects of PPIs on female cancers.

Comparison of long-term outcomes of spinal fusion surgeries supplemented with "topping-off" implants in lumbar degenerative diseases: A systematic review and network meta-analysis

Background Context

Spinal fusion surgery is a common treatment for lumbar degenerative diseases and has been associated with the long-term complication of adjacent segment disease (ASD). In recent years, the "topping-off" technique has emerged as a new surgical method, combining spinal fusion with a hybrid stabilization device (HSD) or interspinous process device (IPD) proximal to the fused vertebrae.

Methods

A literature search using the PubMed, Cochrane Central Register of Controlled Trials, EMBASE, and Web of Science databases identified eligible studies comparing topping-off implant(s) with spinal fusion surgery for lumbar degenerative diseases. Risk of bias was assessed using the Cochrane RoB 2.0 tool for randomized controlled trials and the Newcastle-Ottawa scale for retrospective studies. Each outcome was analyzed using the statistical Confidence in NMA (CINeMA) 1.9.0 software.

Results

17 RCTs and retrospective studies that included 1255 participants and five interventions were identified. The topping-off implants device for intervertebral assisted motion (DIAM; OR = 0.235, p < 0.001), Dynesys (OR = 0.413, p < 0.001), and Coflex (OR = 0.417, p < 0.01) significantly lowered the incidence of radiographic adjacent segment degeneration (RASDeg) compared with spinal fusion surgery alone. Spinal fusion supplemented with DIAM significantly reduced the incidence of clinical adjacent segment disease (CASD) (OR = 0.358, p = 0.032).

Conclusions

Spinal fusion supplemented with DIAM substantially reduced the incidence of radiographic and clinical adjacent segment disease. No significant difference was observed between the treatment comparators for reoperation due to ASD and back pain relief score.

Effectiveness and Safety of Immunosuppressants and Biological Therapy for Chronic Spontaneous Urticaria: A Network Meta-Analysis

Chronic spontaneous urticaria (CSU) is the most common phenotype of chronic urticaria. We compared treatment effects and safety profiles of the medications in patients with CSU. We searched PubMed, MEDLINE, and Web of Science for randomized control trials (RCTs), from 1 January 2000 to 31 July 2021, which evaluated omalizumab and immunosuppressants. Network meta-analyses (NMAs) were performed with a frequentist approach. Outcome assessments considered the efficacy (Dermatology Life Quality Index (DLQI) and weekly urticaria activity score (UAS7)) and tolerability profiles with evaluations of study quality, inconsistencies, and heterogeneity. We identified 14 studies which we included in our direct and indirect quantitative analyses. Omalizumab demonstrated better efficacy in DLQI and UAS7 outcomes compared to a placebo, and UAS7 assessments also demonstrated better outcomes compared to cyclosporine. Alongside this, omalizumab demonstrated relatively lower incidences of safety concerns compared to the other immunosuppressants. Cyclosporin was also associated with higher odds of adverse events than other treatment options. Our findings indicate that omalizumab resulted in greater improvements in terms of the DLQI and UAS7 with good tolerability in CSU patients compared to the other immunosuppressants.

Determinants of coronavirus disease 2019 infection by artificial intelligence technology: A study of 28 countries

Objectives

The coronavirus disease 2019 pandemic has affected countries around the world since 2020, and an increasing number of people are being infected. The purpose of this research was to use big data and artificial intelligence technology to find key factors associated with the coronavirus disease 2019 infection. The results can be used as a reference for disease prevention in practice.

Methods

This study obtained data from the "Imperial College London YouGov Covid-19 Behaviour Tracker Open Data Hub", covering a total of 291,780 questionnaire results from 28 countries (April 1~August 31, 2020). Data included basic characteristics, lifestyle habits, disease history, and symptoms of each subject. Four types of machine learning classification models were used, including logistic regression, random forest, support vector machine, and artificial neural network, to build prediction modules. The performance of each module is presented as the area under the receiver operating characteristics curve. Then, this study further processed important factors selected by each module to obtain an overall ranking of determinants.

Results

This study found that the area under the receiver operating characteristics curve of the prediction modules established by the four machine learning methods were all >0.95, and the RF had the highest performance (area under the receiver operating characteristics curve is 0.988). Top ten factors associated with the coronavirus disease 2019 infection were identified in order of importance: whether the family had been tested, having no symptoms, loss of smell, loss of taste, a history of epilepsy, acquired immune deficiency syndrome, cystic fibrosis, sleeping alone, country, and the number of times leaving home in a day.

Conclusions

This study used big data from 28 countries and artificial intelligence methods to determine the predictors of the coronavirus disease 2019 infection. The findings provide important insights for the coronavirus disease 2019 infection prevention strategies.

The Impact of Various Anti-Osteoporosis Drugs on All-Cause Mortality After Hip Fractures: A Nationwide Population Study

Anti-osteoporosis treatment following hip fractures may reduce the overall mortality rate. However, the effects of different drugs on mortality is still unclear. This population-based cohort study aimed to identify the degree of reduced mortality after various anti-osteoporosis regimens following hip fracture surgery. We conducted this cohort study to identify patients with newly diagnosed osteoporosis and hip fractures from 2009 to 2017 using the Taiwan National Health Insurance Research Database (NHIRD). The subsequent use of anti-osteoporosis medication following hip fracture surgery was collected and analyzed. National death registration records were retrieved to determine mortality. A total of 45,226 new cases of osteoporotic hip fracture were identified. Compared with patients who did not receive further treatment, patients who had ever used oral bisphosphonates (alendronate and risedronate, hazard ratio [HR] 0.81; 95% confidence interval [CI], 0.78-0.84), ibandronate (HR 0.76; 95% CI, 0.67-0.86), zoledronic acid (HR 0.70; 95% CI, 0.64-0.76), and denosumab (HR 0.64; 95% CI, 0.60-0.68) showed lower all-cause mortality rates. Patients treated with bisphosphonates had a lower mortality risk than those treated with selective estrogen receptor modulators (HR 0.81; 95% CI, 0.75-0.87). Patients treated with zoledronic acid showed a lower mortality risk than those treated with oral bisphosphonates (HR 0.89; 95% CI, 0.82-0.97). However, patients receiving denosumab and zoledronic acid did not show a significant difference in mortality (HR 0.94; 95% CI, 0.85-1.03). Different anti-osteoporosis treatments for postsurgical patients were associated with different levels of decline in mortality. Generally, longer durations of drug use were associated with lower mortality. © 2022 American Society for Bone and Mineral Research (ASBMR).

Association of Air Pollution and Weather Factors with Traffic Injury Severity: A Study in Taiwan

Exposure to air pollutants may elevate the injury severity scores (ISSs) for road traffic injuries (RTIs). This multicenter cross-sectional study aimed to investigate the associations between air pollution, weather conditions, and RTI severity. This retrospective study was performed in Taiwan in 2018. The location of each road traffic accident (RTA) was used to determine the nearest air quality monitoring and weather station, and the time of each RTA was matched to the corresponding hourly air pollutant concentration and weather factors. Five multiple logistic regression models were used to compute the risk of sustaining severe injury (ISS ≥ 9). Of the 14,973 patients with RTIs, 2853 sustained severe injury. Moderate or unhealthy air quality index, higher exposure to particulate matter ≤2.5 μm in diameter, bicyclists or pedestrians, greater road width, nighttime, and higher temperature and relative humidity were significant risk factors for severe injury. Exposure to nitrogen oxide and ozone did not increase the risk. Auto occupants and scene-to-hospital time were the protective factors. Sensitivity analyses showed consistent results between air pollutants and the risk of severe injury. Poor air quality and hot and humid weather conditions were associated with severe RTIs. Active commuters were at higher risk of sustaining severe RTI.

Parsing the role of NSP1 in SARS-CoV-2 infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) leads to shutoff of protein synthesis, and nsp1, a central shutoff factor in coronaviruses, inhibits cellular mRNA translation. However, the diverse molecular mechanisms employed by nsp1 as well as its functional importance are unresolved. By overexpressing various nsp1 mutants and generating a SARS-CoV-2 mutant, we show that nsp1, through inhibition of translation and induction of mRNA degradation, targets translated cellular mRNA and is the main driver of host shutoff during infection. The propagation of nsp1 mutant virus is inhibited exclusively in cells with intact interferon (IFN) pathway as well as in vivo, in hamsters, and this attenuation is associated with stronger induction of type I IFN response. Therefore, although nsp1's shutoff activity is broad, it plays an essential role, specifically in counteracting the IFN response. Overall, our results reveal the multifaceted approach nsp1 uses to shut off cellular protein synthesis and uncover nsp1's explicit role in blocking the IFN response.

Reduced All-Cause Mortality with Bisphosphonates Among Post-Fracture Osteoporosis Patients: A Nationwide Study and Systematic Review

We assessed the survival outcomes associated with real-world bisphosphonate use, stratified by fracture site, type, administration, and duration of treatment, among patients with osteoporosis. A systematic review that incorporates our findings was conducted to provide up-to-date evidence on survival outcomes with bisphosphonate treatment in real-world settings. Patients diagnosed with osteoporosis who had been hospitalized for major fractures were identified from Taiwan's National Health Insurance Research Database 2008-2017 and followed until 2018. There were 24,390 new bisphosphonate users who were classified and compared with 76,725 nonusers of anti-osteoporosis medications in terms of survival outcomes using Cox model analysis. An inverse probability of treatment weighted Cox model and landmark analyses for minimizing immortal time bias were also performed. Bisphosphonate users vs. nonusers had a significantly lower mortality risk, regardless of fracture site (hazard ratios (95% confidence intervals) for patients with any major fracture, hip fracture, and vertebral fracture: 0.90 (0.88, 0.93), 0.83 (0.80, 0.86), and 0.86 (0.82, 0.89), respectively). Compared with nonuse, zoledronic acid (0.77 (0.73, 0.82)) was associated with the lowest mortality, followed by ibandronate (0.85 (0.78, 0.93)) and alendronate/risedronate (0.93 (0.91, 0.96)). Using bisphosphonates for ≥ 3 years had lower mortality (0.60 (0.53, 0.67)) than using bisphosphonates for < 3 years (0.98 (0.95, 1.01)). Intravenous bisphosphonates had a lower mortality than that of oral bisphosphonates. Our results are consistent with the systematic review findings among real-world populations. In conclusion, bisphosphonate use, especially persistence to intravenous bisphosphonates (e.g., zoledronic acid), may reduce post-fracture mortality among patients with osteoporosis, particularly those with hip/vertebral fractures. This supports the rational use of bisphosphonates in post-fracture care.

Efficacy and self-similarity of SARS-CoV-2 thermal decontamination

Dry heat decontamination has been shown to effectively inactivate viruses without compromising the integrity of delicate personal protective equipment (PPE), allowing safe reuse and helping to alleviate shortages of PPE that have arisen due to COVID-19. Unfortunately, current thermal decontamination guidelines rely on empirical data which are often sparse, limited to a specific virus, and unable to provide fundamental insight into the underlying inactivation reaction. In this work, we experimentally quantified dry heat decontamination of SARS-CoV-2 on disposable masks and validated a model that treats the inactivation reaction as thermal degradation of macromolecules. Furthermore, upon nondimensionalization, all of the experimental data collapse onto a unified curve, revealing that the thermally driven decontamination process exhibits self-similar behavior. Our results show that heating surgical masks to 70 °C for 5 min inactivates over 99.9% of SARS-CoV-2. We also characterized the chemical and physical properties of disposable masks after heat treatment and did not observe degradation. The model presented in this work enables extrapolation of results beyond specific temperatures to provide guidelines for safe PPE decontamination. The modeling framework and self-similar behavior are expected to extend to most viruses-including yet-unencountered novel viruses-while accounting for a range of environmental conditions.

Parsing the role of NSP1 in SARS-CoV-2 infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the ongoing coronavirus disease 19 (COVID-19) pandemic. Despite its urgency, we still do not fully understand the molecular basis of SARS-CoV-2 pathogenesis and its ability to antagonize innate immune responses. SARS-CoV-2 leads to shutoff of cellular protein synthesis and over-expression of nsp1, a central shutoff factor in coronaviruses, inhibits cellular gene translation. However, the diverse molecular mechanisms nsp1 employs as well as its functional importance in infection are still unresolved. By overexpressing various nsp1 mutants and generating a SARS-CoV-2 mutant in which nsp1 does not bind ribosomes, we untangle the effects of nsp1. We uncover that nsp1, through inhibition of translation and induction of mRNA degradation, is the main driver of host shutoff during SARS-CoV-2 infection. Furthermore, we find the propagation of nsp1 mutant virus is inhibited specifically in cells with intact interferon (IFN) response as well as in-vivo , in infected hamsters, and this attenuation is associated with stronger induction of type I IFN response. This illustrates that nsp1 shutoff activity has an essential role mainly in counteracting the IFN response. Overall, our results reveal the multifaceted approach nsp1 uses to shut off cellular protein synthesis and uncover the central role it plays in SARS-CoV-2 pathogenesis, explicitly through blockage of the IFN response.

Analysis of Dual Combination Therapies Used in Treatment of Hypertension in a Multinational Cohort

IMPORTANCE

More than 1 billion adults have hypertension globally, of whom 70% cannot achieve their hypertension control goal with monotherapy alone. Data are lacking on clinical use patterns of dual combination therapies prescribed to patients who escalate from monotherapy.

OBJECTIVE

To investigate the most common dual combinations prescribed for treatment escalation in different countries and how treatment use varies by age, sex, and history of cardiovascular disease.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study used data from 11 electronic health record databases that cover 118 million patients across 8 countries and regions between January 2000 and December 2019. Included participants were adult patients (ages ≥18 years) who newly initiated antihypertensive dual combination therapy after escalating from monotherapy. There were 2 databases included for 3 countries: the Iqvia Longitudinal Patient Database (LPD) Australia and Electronic Practice-based Research Network 2019 linked data set from South Western Sydney Local Health District (ePBRN SWSLHD) from Australia, Ajou University School of Medicine (AUSOM) and Kyung Hee University Hospital (KHMC) databases from South Korea, and Khoo Teck Puat Hospital (KTPH) and National University Hospital (NUH) databases from Singapore. Data were analyzed from June 2020 through August 2021.

EXPOSURES

Treatment with dual combinations of the 4 most commonly used antihypertensive drug classes (angiotensin-converting enzyme inhibitor [ACEI] or angiotensin receptor blocker [ARB]; calcium channel blocker [CCB]; β-blocker; and thiazide or thiazide-like diuretic).

MAIN OUTCOMES AND MEASURES

The proportion of patients receiving each dual combination regimen, overall and by country and demographic subgroup.

RESULTS

Among 970 335 patients with hypertension who newly initiated dual combination therapy included in the final analysis, there were 11 494 patients from Australia (including 9291 patients in Australia LPD and 2203 patients in ePBRN SWSLHD), 6980 patients from South Korea (including 6029 patients in Ajou University and 951 patients in KHMC), 2096 patients from Singapore (including 842 patients in KTPH and 1254 patients in NUH), 7008 patients from China, 8544 patients from Taiwan, 103 994 patients from France, 76 082 patients from Italy, and 754 137 patients from the US. The mean (SD) age ranged from 57.6 (14.8) years in China to 67.7 (15.9) years in the Singapore KTPH database, and the proportion of patients by sex ranged from 24 358 (36.9%) women in Italy to 408 964 (54.3%) women in the US. Among 12 dual combinations of antihypertensive drug classes commonly used, there were significant variations in use across country and patient subgroup. For example starting an ACEI or ARB monotherapy followed by a CCB (ie, ACEI or ARB + CCB) was the most commonly prescribed combination in Australia (698 patients in ePBRN SWSLHD [31.7%] and 3842 patients in Australia LPD [41.4%]) and Singapore (216 patients in KTPH [25.7%] and 439 patients in NUH [35.0%]), while in South Korea, CCB + ACEI or ARB (191 patients in KHMC [20.1%] and 1487 patients in Ajou University [24.7%]), CCB + β-blocker (814 patients in Ajou University [13.5%] and 217 patients in KHMC [22.8%]), and ACEI or ARB + CCB (147 patients in KHMC [15.5%] and 1216 patients in Ajou University [20.2%]) were the 3 most commonly prescribed combinations. The distribution of 12 dual combination therapies were significantly different by age and sex in almost all databases. For example, use of ACEI or ARB + CCB varied from 873 of 3737 patients ages 18 to 64 years (23.4%) to 343 of 2292 patients ages 65 years or older (15.0%) in South Korea's Ajou University database (P for database distribution by age < .001), while use of ACEI or ARB + CCB varied from 2121 of 4718 (44.8%) men to 1721 of 4549 (37.7%) women in Australian LPD (P for drug combination distributions by sex < .001).

CONCLUSIONS AND RELEVANCE

In this study, large variation in the transition between monotherapy and dual combination therapy for hypertension was observed across countries and by demographic group. These findings suggest that future research may be needed to investigate what dual combinations are associated with best outcomes for which patients.

The association between osteoporosis medications and lowered all-cause mortality after hip or vertebral fracture in older and oldest-old adults: a nationwide population-based study

Background: Osteoporotic fracture is a common public-health problem in ageing societies. Although post-fracture usage of osteoporosis medications may reduce mortality, recent results have been inconsistent. We aimed to examine associations between osteoporosis medication and mortality in older adults, particularly oldest-old adults (>=85 years old).

Methods: Participants aged 65 years old and older newly diagnosed with both osteoporosis and hip or vertebral fractures within 2009-2017 were recruited from the records of 23,455,164 people in Taiwan National Health Insurance Research Database (NHIRD). Osteoporosis medication exposure was calculated after the first-time ambulatory visit with newly diagnosed osteoporosis. Mortality and its specific causes were ascertained from Cause of Death Data. Patients were followed until death or censored at the end of 2018.

Results: A total of 87,935 participants aged 65 years old and over (73.4% female), with a mean 4.13 follow-up years, were included. Taking medication was associated with significantly lower risk of mortality (hip fracture HR 0.75, vertebral fracture HR 0.74), even in the oldest-old adults (hip fracture HR 0.76, vertebral fracture HR 0.72), where a longer duration of taking osteoporosis medication was associated with lower all-cause mortality. Specific causes of mortality were also significantly lower for participants taking osteoporosis medication (cancer HR 0.84 in hip fracture, 0.75 in vertebral fracture; cardiovascular disease HR 0.85 in hip fracture, 0.91 in vertebral fracture).

Conclusions: Osteoporosis medication after hip or vertebral fracture may reduce mortality risk in older adults, notably in oldest-old adults. Encouraging the use of post-fracture osteoporosis medication in healthcare policies is warranted.

Identification and inference for subgroups with differential treatment efficacy from randomized controlled trials with survival outcomes through multiple testing

With the uptake of targeted therapies, instead of the "one-fits-all" approach, modern randomized controlled trials (RCTs) often aim to develop treatments that target a subgroup of patients. Motivated by analyzing the Age-Related Eye Disease Study (AREDS) data, a large RCT to study the efficacy of nutritional supplements in delaying the progression of an eye disease, age-related macular degeneration (AMD), we develop a simultaneous inference procedure to identify and infer subgroups with differential treatment efficacy in RCTs with time-to-event outcomes. Specifically, we formulate the multiple testing problem through contrasts and construct their simultaneous confidence intervals, which appropriately control both within- and across-marker multiplicity. Realistic simulations are conducted using real genotype data to evaluate the method performance under various scenarios. The method is then applied to AREDS to assess the efficacy of antioxidants and zinc combination in delaying AMD progression. Multiple gene regions including ESRRB-VASH1 on chromosome 14 have been identified with subgroups showing differential efficacy. We further validate our findings in an independent subsequent RCT, AREDS2, by discovering consistent differential treatment responses in the targeted and non-targeted subgroups identified from AREDS. This multiple-testing-based simultaneous inference approach provides a step forward to confidently identify and infer subgroups in modern drug development.

Botulinum Toxin Injections for Treatment of Drooling in Children with Cerebral Palsy: A Systematic Review and Meta-Analysis

Background: We aimed to review and analyse the effectiveness and safety of botulinum toxin type A (BoNT-A) injections for drooling in children with cerebral palsy. Data sources: We searched the EMBASE, MEDLINE, Cochrane Database of Systematic Reviews, and Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library) databases from inception to January 2020. Methods: We included randomized controlled trials and observational studies which (1) involved children with cerebral palsy, (2) used BoNT-A for control of drooling, and (3) provided quantitative evaluations of drooling before and after intervention with BoNT-A. Results: Twenty-one trials met the inclusion criteria. Most studies showed that BoNT-A injections are safe and efficacious as a treatment for drooling in children with cerebral palsy. Four trials had sufficient data to pool the results for the meta-analysis. Both the drooling quotient (p = 0.002) and drooling Ffrequency and severity scale (p = 0.004) supported this conclusion. Conclusion: BoNT-A injections are a safe, reversible, effective treatment for drooling control in children with cerebral palsy that can offer effectiveness for more than 3 months with few side effects. The dosage of BoNT-A should not exceed 4 units/kg. Further studies are required to determine the optimal dosage and target glands.

Association Between Social Media Use and Cancer Screening Awareness and Behavior for People Without a Cancer Diagnosis: Matched Cohort Study

BACKGROUND

The use of social media in communications regarding cancer prevention is rapidly growing. However, less is known about the general population's social media use related to cancer screening awareness and behavior for different cancers.

OBJECTIVE

We aimed to examine the relationship between social media use and cancer screening awareness and behavior among people without a cancer diagnosis.

METHODS

Data were collected from the Health Information National Trends Survey 5 Cycle 1 to 3 in the United States (n=12,227). Our study included 10,124 participants without a cancer diagnosis and 3 measures of screening awareness (those who had heard of hepatitis C virus [HCV], human papillomavirus [HPV], and the HPV vaccine) and 4 measures of behavior (those who had prostate-specific antigen tests, Papanicolaou tests for cervical cancer, as well as breast cancer and colon cancer tests). Propensity-score matching was conducted to adjust for the sociodemographic variables between the social media user and nonuser participants. Multivariable logistic regression was used to assess the association of social media use by gender. Jackknife replicate weights were incorporated into the analyses.

RESULTS

Of the 3794 matched participants, 1861 (57.6% weighted) were male, and the mean age was 55.5 (SD 0.42) years. Compared to social media nonusers, users were more likely to have heard of HCV (adjusted odds ratio [aOR]=2.27, 95% CI, 1.29-3.98 and aOR=2.86, 95% CI, 1.51-5.40, for male and female users, respectively) and HPV (aOR=1.82, 95% CI, 1.29-2.58 and aOR=2.35, 95% CI, 1.65-3.33, for male and female users, respectively). In addition, female users were more likely to have heard of the HPV vaccine (aOR=2.06, 95% CI, 1.41-3.00). No significant associations were found between social media use and prostate-specific antigen tests in males, Papanicolaou tests and breast cancer tests in females, or colon cancer tests in both male and female users.

CONCLUSIONS

While social media services can potentially promote cancer screening awareness in the general population, but they did not improve screening behavior after adjusting for socioeconomic status. These findings strengthened our understanding of social media use in targeting health communications for different cancers.

Rejoinder for discussions on correct and logical causal inference for binary and time-to-event outcomes in randomized controlled trials

Our paper differs from previous literature in two ways: 1.We think in terms of clinical consequences, what benefits patients, what harms patients. Our main message is: using a not logic-respecting efficacy measure can potentially harm patients in a randomized controlled trial (RCT), as we prove analytically, and demonstrate with the OAK blood-based tumor mutational burden (bTMB) study. 2.We follow nature, which mixes effects within each treatment arm. Our secondary message is that following nature to mix within each treatment arm first before calculating any efficacy measure between treatments resolves issues. For example, following natural mixing to prove ratio of time is logic-respecting avoids the issue that weights of efficacy measures are implicit solution to an equation that depends on the unknown prognostic effect. More importantly, coding subgroup mixable estimation (SEM) by mixing within each treatment arm first and then calculating efficacy will make marginal and conditional efficacy agree, for logic-respecting efficacy measures (be it a ratio or a difference), no matter the outcome is continuous, binary, or time-to-event. One does not have to choose between marginal and conditional.

The Effectiveness and Safety of Immune Checkpoint Inhibitors in Non-Small Cell Lung Cancer Patients With Stage III/IV: A Multicenter Study

Immune checkpoint inhibitors (ICIs) have been approved to treat patients with various cancer types, including lung cancer, in many countries. This study aims to investigate the effectiveness and safety of ICIs under different treatment conditions of non-small cell lung cancer patients. A population-based retrospective cohort study was conducted using the electronic health records of three medical centers in Taiwan. From January 01, 2016, to November 30, 2018, a total of 91 ICIs and 300 traditional chemotherapy users who had undergone stage III and IV lung cancer treatment were included in the study. We performed the randomized matched pair design by selecting a Chemotherapy subject for each ICI patient in the sample population. All subjects were monitored from the date of taking ICIs or chemotherapy drugs until the event of death, loss to follow-up, or were occurred with any defined adverse events. Kaplan-Meier estimators and cox proportional hazard regression models were used to compute the overall survival, efficacy, and safety of the ICIs group. The median overall survival (OS) in the ICI and Chemo groups after matching was 11.2 months and 10.5 months, respectively. However, the results showed no significant OS differences between ICIs and chemo groups for both before and after matching (HR,1.30; 95%CI, 0.68-2.46; p=0.428 before matching and HR,0.96; 95CI%, 0.64-1.44; p=0.838 after matching). We observed that with the higher amount of PD-L1, the length of the patients’ overall survival was (positive vs. negative PD-L1, HR,0.21; 95%CI, 0.05-0.80; p=0.022). The incidences of serious adverse drug events above grade 3 in the ICIs and traditional chemo groups were 12.7% and 21.5%, respectively. We also found that the number of AEs was less in ICIs than in the Chemo group, and the AEs that occurred after treatments were observed earlier in the ICIs compared to the Chemo group. ICIs drugs were observed to be safer than traditional chemotherapy as they had a lower risk of serious adverse drug events. It is necessary to pay attention to immune-related side effects and provide appropriate treatment. Furthermore, the patient’s physical status and PD-L1 test can be used to evaluate the clinical effectiveness of ICIs.

A cost-utility analysis of avelumab for metastatic Merkel cell carcinoma in Taiwan

BACKGROUND

Metastatic Merkel cell carcinoma (mMCC) has traditionally been managed with palliative chemotherapy regimens or best supportive care (BSC). Avelumab, a novel anti-programmed death-ligand 1 (PD-L1) human monoclonal antibody for mMCC treatment, is being studied in the pivotal JAVELIN Merkel 200 trial.

AIM

Incorporating trial results, this analysis aimed to evaluate the cost-utility of avelumab in Taiwan.

METHODS AND RESULTS

A de novo partitioned-survival model with three key health states related to survival (progression-free disease, progressed disease, and death) was applied in this study. The data of clinical efficacy, safety, and patient utilities were obtained from the JAVELIN Merkel 200 trial, literature review, and Taiwanese clinical expert opinion. Cost-utility analysis was performed, and results were presented as cost per quality-adjusted life year (QALY) gained. For treatment-naïve patients, the incremental cost-effectiveness ratios (ICERs) for avelumab vs BSC and avelumab vs chemotherapy were US$44885.06 and US$42993.06 per QALY gained, respectively. As to treatment-experienced mMCC patients, avelumab was associated with ICERs of US$27243.06 (vs BSC)/US$26557.43 (vs chemotherapy) per QALY gained. All ICERs remained consistently within the willingness-to-pay (WTP) threshold of US$53,333.33 per QALY gained.

CONCLUSION

This study demonstrated avelumab to be a cost-effective treatment option for both treatment-experienced and treatment-naïve mMCC patients with very poor prognosis in Taiwan.

Endogenous Type I interferon signaling plays a pivotal role in restricted SARS-CoV-2 infection in human ACE2 transgenic mice

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become pandemic, resulting in severe morbidity and mortality around the world. COVID-19 pathogenesis includes lung inflammation, cytokine storm and organ failures, but the mechanism underlying the disease remains to be studied. To determine what role(s) the well-characterized type I interferon (IFN-I)-mediated innate antiviral responses might play against SARS-CoV-2 infection, we treated hACE2 transgenic (Tg) mice, AC70 line, with mouse IFN-I receptor-specific monoclonal antibody prior to challenge with 106TCID50 of SARS-CoV-2 (US-WA-1/2020). Both IFN-blocked and-unblocked animals developed clinical signs of disease with body weight loss from day 3 and 100% mortality between 4 and 5 days post-infection with SARS-CoV-2 at high dose (106 TCID50). Although live virus was detected in the lungs and brain of both groups, live virus was detected only in the kidneys, liver, spleen, heart, and gastrointestinal tract of the IFN-blocked group. Elevated expression of proinflammatory cytokines and interferons including IFN-λ were detected in all organs tested in both groups. Immunostaining for SARS-CoV-2 spike protein along with profound histopathological observations in the lungs and brain of both groups show severe COVID-19 disease pathogenesis. Our results show that AC70 Tg mice are highly permissive to SARS-COV-2 infection and develop severe COVID-19. Furthermore, we show type I IFN-mediated signaling pathways play a critical role in restricting viral spread and are ideal for development of medical countermeasures (MCMs) against COVID-19.

Bepridil is potent against SARS-CoV-2 in vitro

Guided by a computational docking analysis, about 30 Food and Drug Administration/European Medicines Agency (FDA/EMA)-approved small-molecule medicines were characterized on their inhibition of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease (Mpro). Of these small molecules tested, six displayed a concentration that inhibits response by 50% (IC50) value below 100 μM in inhibiting Mpro, and, importantly, three, that is, pimozide, ebastine, and bepridil, are basic molecules that potentiate dual functions by both raising endosomal pH to interfere with SARS-CoV-2 entry into the human cell host and inhibiting Mpro in infected cells. A live virus-based modified microneutralization assay revealed that bepridil possesses significant anti-SARS-CoV-2 activity in both Vero E6 and A459/ACE2 cells in a dose-dependent manner with low micromolar effective concentration, 50% (EC50) values. Therefore, the current study urges serious considerations of using bepridil in COVID-19 clinical tests.

Exact simultaneous confidence intervals for logical selection of a biomarker cut-point

This article proposes four new principles for logical biomarker cut-point selection methods to adhere to: subgroup sensibility, sensitivity, specificity, and target monotonicity. At every cut-point value, our method gives confidence intervals not only for the efficacy at that cut-point value, but also efficacies in the marker-positive and marker-negative subgroups defined by that cut-point. These confidence intervals are given simultaneously for all possible cut-point values. Using Alzheimer's disease (AD) and type 2 diabetes (T2DM) as examples, we show our method achieves the four principles. Our method strongly controls familywise type I error rate (FWER) across both levels of multiplicity: the multiplicity of having marker-positive and marker-negative subgroups at each cut-point, and the multiplicity of searching through infinitely many cut-points. This is in contrast to other available methods. The confidence level of our simultaneous confidence intervals is in fact exact (not conservative). An application (app) is available, which implements the method we propose.

A real-world observational study of drug utilization and clinical outcomes of direct-acting antivirals and interferon therapy for hepatitis C treatment in Taiwan

OBJECTIVE

In this study, we investigated the use of direct-acting antivirals (DAAs), medical expenses and clinical outcomes since the initiation of national health insurance coverage in Taiwan.

METHODS

This was a retrospective observational study. We obtained claims data from Taiwan's National Health Insurance Research Database in 2017. Patients diagnosed with hepatitis C with at least two physician visits or one hospitalization were included in the study. Cases were divided into three groups based on the treatment type: traditional treatment (interferon, INF), new drug treatment (DAA) and INF-experienced (INF followed by DAA). We compared the distributions of various cases based on individual demographic variables, hospital type and comorbidities. Trends in medical expenses by treatment type were estimated. We also analyzed clinical outcomes, including rehospitalization and liver function disorders, using a survival analysis method.

RESULTS

Among patients with hepatitis C, the DAA group had a significantly higher proportion of females, a higher mean age and greater disease severity than the INF group. The growth rate of medical expenses was significantly lower in the DAA group. In addition, compared to the INF group, the DAA group and INF-experienced group had significantly lower rehospitalization rates, and the DAA group had a significantly lower risk of liver function disorders. Furthermore, the longer a patient received any form of treatment, the lower was their chance of rehospitalization and liver function disorders.

CONCLUSIONS

In conclusion, our results confirmed that insurance coverage of DAAs led to better clinical outcomes than INF, and this may reduce increases in medical expenses and the risks of rehospitalization and liver function disorders.

WHAT IS KNOWN ON THIS TOPIC

Interferon for hepatitis C has low efficacy with serious side effects, while the efficacy of new oral drugs (direct-acting antivirals, DAAs) is high. DAAs were approved for listing in Taiwan in December 2013, and they have been covered by National Health Insurance since January 2017. Little is known about DAA-related real-world evidence following the coverage of DAAs in Taiwan, including drug utilization, expenditures and safety.

WHAT THIS STUDY ADDS

This study explored three important issues related to DAAs: drug utilization, medical expenses and clinical outcomes following the insurance coverage by using the National Health Insurance Database. Cases were divided into three groups based on the treatment type: traditional treatment (interferon, INF), new drug treatment (DAA) and INF-experienced (INF followed by DAA). After the adjustment of various personal and hospital factors, the DAA group and INF-experienced group had significantly lower rehospitalization rates, and the DAA group had a significantly lower risk of liver function disorders, compared to the interferon group. There was a lower chance of rehospitalization and lower liver function disorder rates with longer treatment.

A Quick Route to Multiple Highly Potent SARS-CoV-2 Main Protease Inhibitors*

The COVID-19 pathogen, SARS-CoV-2, requires its main protease (SC2M^Pro ) to digest two of its translated long polypeptides to form a number of mature proteins that are essential for viral replication and pathogenesis. Inhibition of this vital proteolytic process is effective in preventing the virus from replicating in infected cells and therefore provides a potential COVID-19 treatment option. Guided by previous medicinal chemistry studies about SARS-CoV-1 main protease (SC1M^Pro ), we have designed and synthesized a series of SC2M^Pro inhibitors that contain β-(S-2-oxopyrrolidin-3-yl)-alaninal (Opal) for the formation of a reversible covalent bond with the SC2M^Pro active-site cysteine C145. All inhibitors display high potency with K_i values at or below 100 nM. The most potent compound, MPI3, has as a K_i value of 8.3 nM. Crystallographic analyses of SC2M^Pro bound to seven inhibitors indicated both formation of a covalent bond with C145 and structural rearrangement from the apoenzyme to accommodate the inhibitors. Virus inhibition assays revealed that several inhibitors have high potency in inhibiting the SARS-CoV-2-induced cytopathogenic effect in both Vero E6 and A549/ACE2 cells. Two inhibitors, MPI5 and MPI8, completely prevented the SARS-CoV-2-induced cytopathogenic effect in Vero E6 cells at 2.5-5 μM and A549/ACE2 cells at 0.16-0.31 μM. Their virus inhibition potency is much higher than that of some existing molecules that are under preclinical and clinical investigations for the treatment of COVID-19. Our study indicates that there is a large chemical space that needs to be explored for the development of SC2M^Pro inhibitors with ultra-high antiviral potency.

A Speedy Route to Multiple Highly Potent SARS-CoV-2 Main Protease Inhibitors

The COVID-19 pathogen, SARS-CoV-2, requires its main protease (SC2M ^Pro ) to digest two of its translated polypeptides to form a number of mature proteins that are essential for viral replication and pathogenesis. Inhibition of this vital proteolytic process is effective in preventing the virus from replication in infected cells and therefore provides a potential COVID-19 treatment option. Guided by previous medicinal chemistry studies about SARS-CoV-1 main protease (SC1M ^Pro ), we have designed and synthesized a series of SC2M ^Pro inhibitors that contain β-( S -2-oxopyrrolidin-3-yl)-alaninal (Opal) for the formation of a reversible covalent bond with the SC2M ^Pro active site cysteine C145. All inhibitors display high potency with IC ₅₀ values at or below 100 nM. The most potent compound MPI3 has as an IC ₅₀ value as 8.5 nM. Crystallographic analyses of SC2M ^Pro bound to 7 inhibitors indicated both formation of a covalent bond with C145 and structural rearrangement from the apoenzyme to accommodate the inhibitors. Virus inhibition assays revealed that several inhibitors have high potency in inhibiting the SARS-CoV-2-induced cytopathogenic effect in both Vero E6 and A549 cells. Two inhibitors MP5 and MPI8 completely prevented the SARS-CoV-2-induced cytopathogenic effect in Vero E6 cells at 2.5-5 μM and A549 cells at 0.16-0.31 μM. Their virus inhibition potency is much higher than some existing molecules that are under preclinical and clinical investigations for the treatment of COVID-19. Our study indicates that there is a large chemical space that needs to be explored for the development of SC2M ^Pro inhibitors with extreme potency. Due to the urgent matter of the COVID-19 pandemic, MPI5 and MPI8 may be quickly advanced to preclinical and clinical tests for COVID-19.

Health inequality: a longitudinal study on geographic variations in lung cancer incidence and mortality in Taiwan

Background

This study is aimed toward an analysis of the variations in lung cancer incidence and mortality, adjusted by population factors (age, gender, and year), between administrative areas.

Methods

This is a retrospective study, using 2005–2014 data in each administrative area from the Taiwan Cancer Registry database organized by the Health Promotion Administration. The yearly age-standardized (overall) and crude (stratified by gender and age) incidence/mortality (and their growth rates) for each administrative area were collected and calculated. We used a mixed model to analyze the repeated measurements of yearly incidence and mortality rates and used general linear regression to analyze their growth rates.

Results

It was found that male and elderly populations had significantly higher lung cancer incidence and mortality in Taiwan. After adjusting for gender, age, and calendar year, there were no significant variations in incidence among the administrative areas, while the mortality in Yilan County was significantly higher than that in Taipei City (the capital city of Taiwan). On the other hand, the incidence in the female and younger population and mortality growth rates were higher. The incidence growth rate in Keelung City was significantly lower than that in Taipei City, while there were no significant variations in mortality growth rate among administrative areas.

Conclusions

This study found an inequality in the lung cancer burden among cities in Taiwan, which can serve as the basis for future resource allocations for lung cancer prevention and treatment in Taiwan.

Lung cancer survival and mortality in Taiwan following the initial launch of targeted therapies: an interrupted time series study

OBJECTIVES

Two oral targeted therapies, gefitinib and erlotinib, were first approved and then launched into the market for treatment of late-stage non-small cell lung cancer (NSCLC) in Taiwan in 2003 and 2006, respectively. The aim of this study were to determine the trends in lung cancer burden and examine changes in lung cancer-related survival rates and mortality following the launch of these new drugs.

SETTING

Yearly lung cancer-related data (1994-2013), including incidence, number of newly diagnosed patients, survival rate and mortality, were retrieved from the Taiwan Cancer Registry Database.

DESIGN AND OUTCOME MEASURES

Using a time series design with autoregressive integrated moving average model, we investigated and projected trends in the incidence and early diagnosis of lung cancer in Taiwan. We also estimated the changes in survival rates and mortality following the launch of targeted therapies using interrupted time series and segmented regression models.

RESULTS

The age-standardised incidence of lung cancer increased from 22.53 per 100 000 people in 1994 to 34.09 in 2013, and it was projected to reach 38.98 by 2020. The rate of early-stage NSCLC at diagnosis increased from 12.63% in 2004 to 23.99% in 2013, and it was projected to reach 32.95% by 2020. The 2-year lung cancer survival increased by 19.81% (95% CI 14.90% to 24.71%) 3 years following the launch of gefitinib. Lung cancer mortality declined by 5.97% (95% CI -8.20% to -3.73%) 3 years following the launch of gefitinib.

CONCLUSIONS

Lung cancer survival rate increased and mortality decreased significantly following the launch of gefitinib and erlotinib in Taiwan.

Budget impact analysis of osteoporosis medications for primary prevention of fractures in Taiwan

INTRODUCTION

Taiwan's national health insurance currently only covers the use of osteoporosis drugs for the secondary prevention of fractures and does not provide coverage for primary prevention. The purpose of this study is to develop a model for analyzing the budgetary impact of the use of osteoporosis medications of primary prevention.

METHODS

The budget impact model in this study is the "actual medication cost" minus the "medical expenses for all types of fractures that can be avoided by taking osteoporosis medications." We developed six possible insurance payment plans for primary prevention based on the age of the patients and T-scores and performed eleven steps to estimate the budget impact of each payment plan.

RESULTS

The results of this study indicated that there may be 71,220 (T-score ≤ - 3.0, 75 + y/o) to 157,515 (T-score ≤ - 2.5, 65 + y/o) people using the drugs, and the budget impact may be US$26.28-58.98 million in 2019. However, the payment plans may avoid 492-766 fracture events and save medical expenditures for fracture treatment by US$1.30-2.02 million. The average costs for primary prevention within a year will be US$53,386-77,006.

CONCLUSION

The budget impact of using osteoporosis medications to primary prevention of fractures is significant, but it can be compensated due to savings in fracture treatment costs.

Comparative effectiveness and cost-effectiveness of three first-line EGFR-tyrosine kinase inhibitors: Analysis of real-world data in a tertiary hospital in Taiwan

Introduction

Comparison of the effectiveness and cost-effectiveness of three first-line EGFR-tyrosine kinase inhibitors (TKIs) would improve patients’ clinical benefits and save costs. Using real-world data, this study attempted to directly compare the effectiveness and cost-effectiveness of first-line afatinib, erlotinib, and gefitinib.

Methods

During May 2011-December 2017, all patients with non-small cell lung cancer (NSCLC) visiting a tertiary center were invited to fill out the EuroQol five-dimension (EQ-5D) questionnaires and World Health Organization Quality of Life, brief version (WHOQOL-BREF), and received follow-ups for survival and direct medical costs. A total of 379 patients with EGFR mutation-positive advanced NSCLC under first-line TKIs were enrolled for analysis. After propensity score matching for the patients receiving afatinib (n = 48), erlotinib (n = 48), and gefitinib (n = 96), we conducted the study from the payers’ perspective with a lifelong time horizon.

Results

Patients receiving afatinib had the worst lifetime psychometric scores, whereas the differences in quality-adjusted life expectancy (QALE) were modest. Considering 3 treatments together, afatinib was dominated by erlotinib. Erlotinib had an incremental cost-effectiveness of US$17,960/life year and US$12,782/QALY compared with gefitinib. Acceptability curves showed that erlotinib had 58.6% and 78.9% probabilities of being cost-effective given a threshold of 1 Taiwanese per capita GDP per life year and QALY, respectively.

Conclusion

Erlotinib appeared to be cost-effective. Lifetime psychometric scores may provide additional information for effectiveness evaluation.

Comprehensive value assessment of drugs using a multi-criteria decision analysis: An example of targeted therapies for metastatic colorectal cancer treatment

OBJECTIVE

This study is aimed toward establishing a decision-making model with multiple criteria for appraisal and reimbursement to compare the attitudes of different stakeholders toward various dimensions and criteria and to evaluate the five targeted therapies (bevacizumab, cetuximab, panitumumab, aflibercept, and regorafenib) for metastatic colorectal cancer.

METHOD

This study is a multi-criteria decision analysis (MCDA) using a model that includes three dimensions and nine criteria. Both the overall and individual scores of the respective targeted therapies in different dimensions and criteria were calculated. A sensitivity analysis was carried out in order to evaluate the robustness of the research results. An interview-based questionnaire survey was applied to obtain the performance information for the targeted therapies and the weights of the dimensions and criteria.

RESULTS

Overall, the clinical dimension had the highest weight, followed by the economic dimension, and finally, the social dimension. In the clinical dimension, the "comparative efficacy" criterion had the highest weight; in the economic dimension, the "cost-effectiveness" criterion" was given the greatest importance; in the social dimension, the "social concern and patient needs" criterion was given more emphasis. The overall values ranked from high to low as follows: cetuximab (overall score 3.3666), bevacizumab (3.3043), panitumumab (3.2030), aflibercept (2.8923) and regorafenib (2.8366).

CONCLUSIONS

A comprehensive value assessment system combining "multi-dimensional criteria," "multi-perspectives," and an "integrative assessment" is necessary to evaluate the value of medicines. The results showed not only the order of weights of different dimensions or criteria, but also the rankings of the value of the targeted therapies.

Effects of removing reimbursement restrictions on targeted therapy accessibility for non-small cell lung cancer treatment in Taiwan: an interrupted time series study

INTERVENTIONS

Targeted therapies have been proven to provide clinical benefits to patients with metastatic non-small cell lung cancer (NSCLC). Gefitinib was initially approved and reimbursed as a third-line therapy for patients with advanced NSCLC by the Taiwan National Health Insurance (NHI) in 2004; subsequently it became a second-line therapy (in 2007) and further a first-line therapy (in 2011) for patients with epidermal growth factor receptor mutation-positive advanced NSCLC. Another targeted therapy, erlotinib, was initially approved as a third-line therapy in 2007, and it became a second-line therapy in 2008.

OBJECTIVES

This study is aimed towards an exploration of the impacts of the Taiwan NHI reimbursement policies (removing reimbursement restrictions) related to accessibility of targeted therapies.

SETTING

We retrieved 2004-2013 claims data for all patients with lung cancer diagnoses from the NHI Research Database.

DESIGN AND OUTCOME MEASURES

Using an interrupted time series design and segmented regression, we estimated changes in the monthly prescribing rate by patient number and market shares by cost following each modification of the reimbursement policy for gefitinib and erlotinib for NSCLC treatment.

RESULTS

Totally 92 220 patients with NSCLC were identified. The prescribing rate of the targeted therapies increased by 15.58%, decreased by 10.98% and increased by 6.31% following the introduction of gefitinib as a second-line treatment in 2007, erlotinib as a second-line treatment in 2008 and gefitinib as as first line treatment in 2011, respectively. The average time to prescription reduced by 65.84% and 41.59% following coverage of erlotinib by insurance and gefitinib/erlotinib as second-line treatments in 2007-2008 and following gefitinib as the first-line treatment in 2011.

CONCLUSIONS

The changes in reimbursement policies had a significant impact on the accessibility of targeted therapies for NSCLC treatment. Removing reimbursement restrictions can significantly increase the level and the speed of drug accessibility.

Use of assisted reproductive technologies before and after the Artificial Reproduction Act in Taiwan

Background

Low birth rates and infertility are growing concerns for many countries. The Artificial Reproduction Act (ARA) was implemented in 2007 to better support the use of assisted reproductive technology (ART) in Taiwan. This study aims to examine trends in the use of ART and to determine impacts of the ARA on ART use.

Method

This study used data from the Health Promotion Administration in Taiwan. We used auto-regression models to examine the recent trends (1998–2017) in fertility related indicators and the use of ART. An interrupted time series design and segmented linear regression models were applied to analyze the changes in number of ART treatment cycles and birth rates by ART following the ARA.

Results

The number of births by ART has gradually increased, with an annual growth rate of 21.55%. The rate of births by ART increased from 0.86% in 1998 to 1.44% in 2007, and to 4.33% in 2016 (annual growth rate: 41.23%). We estimated a relative increase of 78.51% (95%CI: 46.13%, 110.90%) in the number of births by ART and a relative increase of 35.67% (95%CI: 18.87%, 52.47%) in rate of births by ART 5 years following the ARA was implemented.

Conclusion

ART has been seen as an approach to improve fertility. Our analysis suggests that the ART use and births associated from ART use both increased in Taiwan following the implementation of ARA. This experience in Taiwan may offer important lessons for other countries that are facing low fertility challenges.