Elimination of Hepatitis C Virus in a Dialysis Population: A Collaborative Care Model in Taiwan.

RATIONALE & OBJECTIVE: Hemodialysis facilities are high-risk environments for the spread of hepatitis C virus (HCV). Eliminating HCV from all dialysis facilities in a community may be achieved more effectively under a collaborative care model. STUDY DESIGN: Quality improvement study of multidisciplinary collaborative care teams including nephrologists, gastroenterologists, and public health practitioners. SETTING & PARTICIPANTS: All dialysis patients in Changhua County, Taiwan were treated using an interdisciplinary collaborative care model implemented within a broader Changhua-Integrated Program to Stop HCV Infection (CHIPS-C). QUALITY IMPROVEMENT ACTIVITIES: Provision of an HCV care cascade to fill 3 gaps, including screening and testing, diagnosis, and universal direct-acting antiviral (DAA) treatment implemented by collaborating teams of dialysis practitioners and gastroenterologists working under auspices of Changhua Public Health Bureau. OUTCOME: Outcome measures included quality indicators pertaining to 6 steps in HCV care ranging from HCV screening to treatment completion to cure. ANALYTICAL APPROACH: A descriptive analysis. RESULTS: A total of 3,657 patients from 31 dialysis facilities were enrolled. All patients completed HCV screening. The DAA treatment initiation rate and completion rate were 88.9% and 94.0%, respectively. The collaborative care model achieved a cure rate of 166 (96.0%) of 173 patients. No virologic failure occurred. The cumulative treatment ratios for patients with chronic HCV infection increased from 5.3% before interferon-based therapy (2017) to 25.6% after restricted provision of DAA (2017-2018), and then to 89.1% after universal access to DAA (2019). LIMITATIONS: Unclear impact of this collaborative care program on incident dialysis patients entering dialysis facilities each year and on patients with earlier stages of chronic kidney disease. CONCLUSIONS: A collaborative care model in Taiwan increased the rates of diagnosis and treatment for HCV in dialysis facilities to levels near those established by the World Health Organization.

Containing COVID-19 Among 627,386 Persons in Contact With the Diamond Princess Cruise Ship Passengers Who Disembarked in Taiwan: Big Data Analytics.

BACKGROUND: Low infection and case-fatality rates have been thus far observed in Taiwan. One of the reasons for this major success is better use of big data analytics in efficient contact tracing and management and surveillance of those who require quarantine and isolation. OBJECTIVE: We present here a unique application of big data analytics among Taiwanese people who had contact with more than 3000 passengers that disembarked at Keelung harbor in Taiwan for a 1-day tour on January 31, 2020, 5 days before the outbreak of coronavirus disease (COVID-19) on the Diamond Princess cruise ship on February 5, 2020, after an index case was identified on January 20, 2020. METHODS: The smart contact tracing-based mobile sensor data, cross-validated by other big sensor surveillance data, were analyzed by the mobile geopositioning method and rapid analysis to identify 627,386 potential contact-persons. Information on self-monitoring and self-quarantine was provided via SMS, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) tests were offered for symptomatic contacts. National Health Insurance claims big data were linked, to follow-up on the outcome related to COVID-19 among those who were hospitalized due to pneumonia and advised to undergo screening for SARS-CoV-2. RESULTS: As of February 29, a total of 67 contacts who were tested by reverse transcription-polymerase chain reaction were all negative and no confirmed COVID-19 cases were found. Less cases of respiratory syndrome and pneumonia were found after the follow-up of the contact population compared with the general population until March 10, 2020. CONCLUSIONS: Big data analytics with smart contact tracing, automated alert messaging for self-restriction, and follow-up of the outcome related to COVID-19 using health insurance data could curtail the resources required for conventional epidemiological contact tracing.

Hurdle Poisson Regression Model for Identifying Factors Related to Noncompliance and Waiting Time for Confirmatory Diagnosis in Colorectal Cancer Screening.

OBJECTIVES: Population-based colorectal cancer (CRC) screening programs that use a fecal immunochemical test (FIT) are often faced with a noncompliance issue and its subsequent waiting time (WT) for those FIT positives complying with confirmatory diagnosis. We aimed to identify factors associated with both of the correlated problems in the same model. METHODS: A total of 294,469 subjects, either with positive FIT test results or having a family history, collected from 2004 to 2013 were enrolled for analysis. We applied a hurdle Poisson regression model to accommodate the hurdle of compliance and also its related WT for undergoing colonoscopy while assessing factors responsible for the mixture of the two outcomes. RESULTS: The effect on compliance and WT varied with contextual factors, such as geographic areas, type of screening units, and level of urbanization. The hurdle score, representing the risk score in association with noncompliance, and the WT score, reflecting the rate of taking colonoscopy, were used to classify subjects into each of three groups representing the degree of compliance and the level of health awareness. CONCLUSION: Our model was not only successfully applied to evaluating factors associated with the compliance and the WT distribution, but also developed into a useful assessment model for stratifying the risk and predicting whether and when screenees comply with the procedure of receiving confirmatory diagnosis given contextual factors and individual characteristics.

Quantile-based fecal hemoglobin concentration for assessing colorectal neoplasms with 1,263,717 Taiwanese screenees.

BACKGROUND: Although fecal hemoglobin concentration (f-Hb) was highly associated with the risk of colorectal neoplasms, current studies on this subject are hampered by skewedness of the data and the ordinal property of f-Hb has not been well studied yet. Our aim was to develop a quantile-based method to estimate adjusted percentiles (median) of fecal hemoglobin concentration and their derived prediction for the risk of multistage outcomes of colorectal disease. METHODS: We used a 6-year follow-up cohort of Taiwanese nationwide colorectal screening program with fecal immunochemical testing (FIT) to obtain fecal hemoglobin concentration and applied accelerated failure time multi-variable analyses to make the comparison of adjusted median and other percentitles of fecal hemoglobin across four categories of colorectal carcinogenesis. We then predicted the risk of colorectal neoplasms on the basis of the corresponding percentile values by using accelerated failure time model with Bayesian inversion method. RESULTS: The adjusted median fecal hemoglobin concentration of nonadvanced adenoma, advanced adenoma, and colorectal cancer were 57, 82, and 163 µg/g feces as opposed to 0 µg/g feces for the normal group. At 90 µg/g of f-Hb, the highly suspected cut-off for colorectal disease, the risks were 17% for non-advanced adenoma, 6% for advanced adenoma, and 9% for CRC. Life-time risks of each colorectal neoplasm were derived by percentiles of fecal hemoglobin concentration. CONCLUSION: Covariate-adjusted risk stratification for multistage outcomes of colorectal neoplasia were provided by using the quantiles of fecal hemoglobin concentration, yielding the estimated life-time risks of 25th to 75th quantitles, ranging from 0.5 to 44% for colorectal cancer, 0.2 to 46% for non-advanced adenoma, and 0.1 to 20% for advanced adenoma.

Rolling-out Screening Volume Affecting Compliance Rate and Waiting Time of FIT-based Colonoscopy.

BACKGROUND AND STUDY AIMS: The population-based colorectal cancer screening program with fecal immunochemical test (FIT) from the inaugural period to the rolling-out period may create a higher demand for colonoscopies, but such a change has not been quantified. We intended to assess the change in the compliance rate and the waiting time (WT) for a colonoscopy and the associated geographic and institutional variations across the 2 periods. MATERIALS AND METHODS: Data from the Taiwanese nationwide colorectal cancer screening program were analyzed. The data included a total of 46,235 FIT-positive cases of 1,258,560 tests in the inaugural period (2004 to 2009) and 270,700 FIT-positive cases of 3,723,789 tests in the rolling-out period (2010 to 2013). The compliance rate and WT for colonoscopy after positive FIT was ascertained and compared between the 2 periods. RESULTS: The rolling-out period resulted in a decline of 16.0% for compliance rate and yielded an additional 1,778,499 waiting days with variation across geography and institution. After adjusting for relevant factors, a decrease in compliance rate by 8.5% and an increase of 714,648 waiting days were still noted. In the rolling-out period, a remarkable decline in compliance rate by 9.8% was found in middle Taiwan, and the longest WT (1,260,109 d) was observed in southern Taiwan. Screening at public health centers led to a 19% decrease in compliance rate and an increase of 2,546,746 waiting days. CONCLUSIONS: The decrease in compliance rate and an increase in the WT with variation across geography and institution resulting from the increased volume of rolling-out FIT screening provide an insight into optimal resource allocation of clinical capacity for colonoscopy.

Planning, implementing, and evaluating Hepatitis C virus elimination via collaborative community-based care cascade: age-period-cohort model for estimating demand from antecedent anti-HCV survey.

BACKGROUND: Estimating the demand for HCV care cascade plays an important role in planning, monitoring, and assessing the performance of introducing a new community-based hepatitis C virus (HCV) elimination program but such an analytic and systematic approach has been barley addressed. METHODS: A new collaborative care program for HCV elimination in the Changhua Community of Taiwan has been offered to a total of 895,353 residents since 2018. To grasp the variation of demand for HCV care cascade across demographic and geographic features in the planning stage, we applied the age-period-cohort spatial model to the antecedent anti-HCV survey enrolling 123,617 participants aged 30 years or older between 2005 and 2018. Based on this precise denominator, we then employed a "before-and-after" study design to routinely evaluate whether the WHO criteria of 90% RNA positive diagnosis and 80% successful treatments could be reached. RESULTS: The overall demand for HCV care cascade was 4.28% (HCV infection) of the underlying population but a declining trend was noted. The early cohort had a higher demand, whereas the demand of the young cohort decreased with each passing year. The demand also differed by township. The demand, allowing for these variations, for antiviral treatment was 22,362, yielding the WHO target of 12,880 for achieving HCV elimination. With 11,844 successful treatments, the effectiveness of elimination has already reached 92% (11,844/12,880) by the end of 2022. CONCLUSIONS: The demand for HCV care cascade allows health care decision-makers to timely and properly assess the performance of a novel community-based collaborative care program in achieving HCV elimination.

The Bayesian Susceptible-Exposed-Infected-Recovered model for the outbreak of COVID-19 on the Diamond Princess Cruise Ship.

The outbreak of COVID-19 on the Diamond Princess Cruise Ship provides an unprecedented opportunity to estimate its original transmissibility with basic reproductive number (R0) and the effectiveness of containment measures. We developed an ordinary differential equation-based Susceptible-Exposed-Infected-Recovery (SEIR) model with Bayesian underpinning to estimate the main parameter of R0 determined by transmission coefficients, incubation period, and the recovery rate. Bayesian Markov Chain Monte Carlo (MCMC) estimation method was used to tackle the parameters of uncertainty resulting from the outbreak of COVID-19 given a small cohort of the cruise ship. The extended stratified SEIR model was also proposed to elucidate the heterogeneity of transmission route by the level of deck with passengers and crews. With the application of the overall model, R0 was estimated as high as 5.70 (95% credible interval: 4.23-7.79). The entire epidemic period without containment measurements was approximately 47 days and reached the peak one month later after the index case. The partial containment measure reduced 63% (95% credible interval: 60-66%) infected passengers. With the deck-specific SEIR model, the heterogeneity of R0 estimates by each deck was noted. The estimated R0 figures were 5.18 for passengers (5-14 deck), mainly from the within-deck transmission, and 2.46 for crews (2-4 deck), mainly from the between-deck transmission. Modelling the dynamic of COVID-19 on the cruise ship not only provides an insight into timely evacuation and early isolation and quarantine but also elucidates the relative contributions of different transmission modes on the cruise ship though the deck-stratified SEIR model. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1007/s00477-020-01968-w).

Evaluating Clinical Efficacy of Antiviral Therapy for COVID-19: A Surrogate Endpoint Approach.

INTRODUCTION: Efficient evaluation with an early surrogate endpoint, taking into account the process of disease evolution, may not only clarify inconsistent or underpowered results but also provide a new insight into the exploration of a new antiviral therapy for treating COVID-19 patients. METHODS: We assessed the dynamics of COVID-19 disease spectrum, commencing from low-risk (no or low oxygen supplement), medium-risk (non-invasive ventilator or high oxygen supplement), and high-risk (extracorporeal membrane oxygenation or invasive ventilator) risk state on enrollment, and then the subsequent progression and regression of risk states until discharge or death. The efficacy of antiviral therapy in altering the dynamics was assessed by using the high-risk state as a surrogate endpoint based on the data retrieved from the two-arm Adaptive Covid-19 Treatment Trial. RESULTS: Using the high-risk state as a surrogate endpoint, remdesivir treatment led to a decrease in the high-risk COVID-19 state by 34.8% (95% CI 26.7-42.0%) for a 14-day period and 29.3% (95% CI 28.8-29.8%) up to 28 days, which were consistent with a statistically significant reduction of death by 30.5% (95% CI 6.6, 50.9%) up to a 28-day period. The estimates of numbers needed to be treated were 100.9 (95% CI 88.1, 115.7) for using the high-risk COVID-19 state as a surrogate endpoint for a 14-day period and 133.3 (95% CI 112.5, 158.0) were required for averting one death from COVID-19 up to 28 days. CONCLUSIONS: We demonstrate the expedient use of the high-risk COVID-19 disease status as a surrogate endpoint for evaluating the primary outcome of the earliest death.

Sojourn-time-corrected receiver operating characteristic curve (ROC) for prostate specific antigen (PSA) test in population-based prostate cancer screening.

Evaluating the performance of serum prostate-specific antigen (PSA) test in population-based screening with receiver operating characteristics (ROC) curve often neglects the time dimension. Asymptomatic cases with negative PSA test would have been missed if sojourn time is not taken into account to allow for cases surfacing into the clinical phase. Data included 20,796 men with PSA test at the first screening round was used from population-based Finnish prostate cancer screening trial during 1996-1999. Cancers detected at the first screen, together with interval cancers ascertained during 4-year follow-up were expediently used to estimate sensitivity and specificity. A sojourn-time-corrected model was applied to estimating the possible false negative cases for those with PSA < 4 ng/ml for correcting the ROC curve. The estimated sensitivity estimate was reduced from 94.4% without correction to 68.8% with correction but the estimated specificity was identical (89.4% vs. 89.2%) at cutoff of 3 ng/ml. The corrected area under curve (AUC) [77.0% (74.9-79.1%)] of the PSA test was significantly lower than the uncorrected AUC [95.9% (95.3-96.6%)]. The failure of considering the time since last negative screen due to incomplete ascertainment for asymptomatic cancer led to the overestimation of PSA test performance that further affects the cut-off value of PSA tests for population-based prostate cancer screening.