Estimation of trajectory of protective efficacy in infectious disease prevention trials using recurrent event times

In studies of infectious disease prevention, the level of protective efficacy of medicinal products such as vaccines and prophylactic drugs tends to vary over time. Many products require administration of multiple doses at scheduled times, as opposed to one-off or continual intervention. Accurate information on the trajectory of the level of protective efficacy over time facilitates informed clinical recommendations and implementation strategies, for example, with respect to the timing of administration of the doses. Based on concepts from pharmacokinetic and pharmacodynamic modeling, we propose a non-linear function for modeling the trajectory after each dose. The cumulative effect of multiple doses of the products is captured by an additive series of the function. The model has the advantages of parsimony and interpretability, while remaining flexible in capturing features of the trajectories. We incorporate this series into the Andersen-Gill model for analysis of recurrent event time data and compare it with alternative parametric and non-parametric functions. We use data on clinical malaria disease episodes from a trial of four doses of an anti-malarial drug combination for chemoprevention to illustrate, and evaluate the performance of the methods using simulation. The proposed method out-performed the alternatives in the analysis of real data in terms of Akaike and Bayesian Information Criterion. It also accurately captured the features of the protective efficacy trajectory such as the area under curve in simulations. The proposed method has strong potential to enhance the evaluation of disease prevention measures and improve their implementation strategies.

A semiparametric joint model for cluster size and subunit-specific interval-censored outcomes

Clustered data frequently arise in biomedical studies, where observations, or subunits, measured within a cluster are associated. The cluster size is said to be informative, if the outcome variable is associated with the number of subunits in a cluster. In most existing work, the informative cluster size issue is handled by marginal approaches based on within-cluster resampling, or cluster-weighted generalized estimating equations. Although these approaches yield consistent estimation of the marginal models, they do not allow estimation of within-cluster associations and are generally inefficient. In this paper, we propose a semiparametric joint model for clustered interval-censored event time data with informative cluster size. We use a random effect to account for the association among event times of the same cluster as well as the association between event times and the cluster size. For estimation, we propose a sieve maximum likelihood approach and devise a computationally-efficient expectation-maximization algorithm for implementation. The estimators are shown to be strongly consistent, with the Euclidean components being asymptotically normal and achieving semiparametric efficiency. Extensive simulation studies are conducted to evaluate the finite-sample performance, efficiency and robustness of the proposed method. We also illustrate our method via application to a motivating periodontal disease dataset.

Modelling non-linear patterns of time-varying intervention effects on recurrent events in infectious disease prevention studies

Protective efficacy of vaccines and pharmaceutical products for prevention of infectious diseases usually vary over time. Information on the trajectory of the level of protection is valuable. We consider a parsimonious, non-linear and non-monotonic function for modelling time-varying intervention effects and compare it with several alternatives. The cumulative effects of multiple doses of intervention over time can be captured by an additive series of the function. We apply it to the Andersen-Gill model for analysis of recurrent time-to-event data. We re-analyze data from a trial of intermittent preventive treatment for malaria to illustrate and evaluate the method by simulation.

A sequential test for assessing the effectiveness of response strategies during an emerging epidemic

In epidemiology, the fatality rate is an important indicator of disease severity and has been used to evaluate the effects of new treatments. During an emerging epidemic with limited resources, monitoring the changes in fatality rate can also provide signals on the evaluation of government policies and healthcare quality, which helps to guide public health decision. A statistical test is developed in this paper to detect changes in fatality rate over time during the course of an emerging infectious disease. A major advantage of the proposed test is that it only requires the regularly reported numbers of deaths and recoveries, which meets the actual need as detailed surveillance data are hard to collect during the course of an emerging epidemic especially the deadly infectious diseases with large magnitude. In addition, with the sequential testing procedure, the effective measures can be detected at the earliest possible time to provide guidance to policymakers for swift action. Simulation studies showed that the proposed test performs well and is sensitive in picking up changes in the fatality rate. The test is applied to the 2014-2016 Ebola outbreak in Sierra Leone for illustration.

A novel method to monitor COVID-19 fatality rate in real-time, a key metric to guide public health policy

An accurate estimator of the real-time fatality rate is warranted to monitor the progress of ongoing epidemics, hence facilitating the policy-making process. However, most of the existing estimators fail to capture the time-varying nature of the fatality rate and are often biased in practice. A simple real-time fatality rate estimator with adjustment for reporting delays is proposed in this paper using the fused lasso technique. This approach is easy to use and can be broadly applied to public health practice as only basic epidemiological data are required. A large-scale simulation study suggests that the proposed estimator is a reliable benchmark for formulating public health policies during an epidemic with high accuracy and sensitivity in capturing the changes in the fatality rate over time, while the other two commonly-used case fatality rate estimators may convey delayed or even misleading signals of the true situation. The application to the COVID-19 data in Germany between January 2020 and January 2022 demonstrates the importance of the social restrictions in the early phase of the pandemic when vaccines were not available, and the beneficial effects of vaccination in suppressing the fatality rate to a low level since August 2021 irrespective of the rebound in infections driven by the more infectious Delta and Omicron variants during the fourth wave.

A sequential test to compare the real-time fatality rates of a disease among multiple groups with an application to COVID-19 data

Infectious diseases, such as the ongoing COVID-19 pandemic, pose a significant threat to public health globally. Fatality rate serves as a key indicator for the effectiveness of potential treatments or interventions. With limited time and understanding of novel emerging epidemics, comparisons of the fatality rates in real-time among different groups, say, divided by treatment, age, or area, have an important role to play in informing public health strategies. We propose a statistical test for the null hypothesis of equal real-time fatality rates across multiple groups during an ongoing epidemic. An elegant property of the proposed test statistic is that it converges to a Brownian motion under the null hypothesis, which allows one to develop a sequential testing approach for rejecting the null hypothesis at the earliest possible time when statistical evidence accumulates. This property is particularly important as scientists and clinicians are competing with time to identify possible treatments or effective interventions to combat the emerging epidemic. The method is widely applicable as it only requires the cumulative number of confirmed cases, deaths, and recoveries. A large-scale simulation study shows that the finite-sample performance of the proposed test is highly satisfactory. The proposed test is applied to compare the difference in disease severity among Wuhan, Hubei province (exclude Wuhan) and mainland China (exclude Hubei) from February to March 2020. The result suggests that the disease severity is potentially associated with the health care resource availability during the early phase of the COVID-19 pandemic in mainland China.

Inclusion of unexposed subjects improves the precision and power of self-controlled case series method

The self-controlled case series is an important method in the studies of the safety of biopharmaceutical products. It uses the conditional Poisson model to make comparison within persons. In models without adjustment for age (or other time-varying covariates), cases who are never exposed to the product do not contribute any information to the estimation. We provide analytic proof and simulation results that the inclusion of unexposed cases in the conditional Poisson model with age adjustment reduces the asymptotic variance of the estimator of the exposure effect and increases power. We re-analysed a vaccine safety dataset to illustrate.

Statistical inference in matched case-control studies of recurrent events

BACKGROUND

The concurrent sampling design was developed for case-control studies of recurrent events. It involves matching for time. Standard conditional logistic-regression (CLR) analysis ignores the dependence among recurrent events. Existing methods for clustered observations for CLR do not fit the complex data structure arising from the concurrent sampling design.

METHODS

We propose to break the matches, apply unconditional logistic regression with adjustment for time in quintiles and residual time within each quintile, and use a robust standard error for observations clustered within persons. We conducted extensive simulation to evaluate this approach and compared it with methods based on CLR. We analysed data from a study of childhood pneumonia to illustrate the methods.

RESULTS

The proposed method and CLR methods gave very similar point estimates of association and showed little bias. The proposed method produced confidence intervals that achieved the target level of coverage probability, whereas the CLR methods did not, except when disease incidence was low.

CONCLUSIONS

The proposed method is suitable for the analysis of case-control studies with recurrent events.

Estimation of the primary, secondary and composite effects of malaria vaccines using data on multiple clinical malaria episodes

BACKGROUND

An effective malaria vaccine affects the risk of malaria directly, through the vaccine-induced immune response (the primary effect), and indirectly, as a consequence of reduced exposure to malaria infection and disease, leading to slower acquisition of natural immunity (the secondary effect). The beneficial primary effect may be offset by a negative secondary effect, resulting in a smaller or nil composite effect. Reports of malaria vaccine trials usually present only the composite effect. We aimed to demonstrate how the primary and secondary effects can also be estimated from trial data.

METHODS

We propose an enhancement to the conditional frailty model for the estimation of primary effect using data on disease episodes. We use the Andersen-Gill model to estimate the composite effect. We consider taking the ratio of the hazard ratios to estimate the secondary effect. We used directed acyclic graphs and data from a randomized trial of the RTS,S/AS02 malaria vaccine to illustrate the problems and solutions. Time-varying effects were estimated by partitioning the follow-up into four time periods.

RESULTS

The primary effect estimates from our proposed model were consistently stronger than the conditional frailty model in the existing literature. The primary effect of the vaccine was consistently stronger than the composite effect across all time periods. Both the primary and composite effects were stronger in the first three months, with hazard ratios (95% confidence interval) 0.62 (0.49-0.79) and 0.68 (0.54-0.84), respectively; the hazard ratios weakened over time. The secondary effect appeared mild, with hazard ratio 1.09 (1.02-1.16) in the first three months.

CONCLUSIONS

The proposed analytic strategy facilitates a more comprehensive interpretation of trial data on multiple disease episodes. The RTS,S/AS02 vaccine had modest primary and secondary effects that waned over time, but the composite effect in preventing clinical malaria remained positive up to the end of the study.

CLINICAL TRIALS REGISTRATION

ClinicalTrials.gov NCT00197041.

Survival analysis with change-points in covariate effects

We apply a maximal likelihood ratio test for the presence of multiple change-points in the covariate effects based on the Cox regression model. The covariate effect is assumed to change smoothly at one or more unknown change-points. The number of change-points is inferred by a sequential approach. Confidence intervals for the regression and change-point parameters are constructed by a bootstrap method based on Bernstein polynomials conditionally on the number of change-points. The methods are assessed by simulations and are applied to two datasets.

Bias control in the analysis of case–control studies with incidence density sampling

Background

Previous simulation studies of the case–control study design using incidence density sampling, which required individual matching for time, showed biased estimates of association from conditional logistic regression (CLR) analysis; however, the reason for this is unknown. Separately, in the analysis of case–control studies using the exclusive sampling design, it has been shown that unconditional logistic regression (ULR) with adjustment for an individually matched binary factor can give unbiased estimates. The validity of this analytic approach in incidence density sampling needs evaluation.

Methods

In extensive simulations using incidence density sampling, we evaluated various analytic methods: CLR with and without a bias-reduction method, ULR with adjustment for time in quintiles (and residual time within quintiles) and ULR with adjustment for matched sets and bias reduction. We re-analysed a case–control study of Haemophilus influenzae type B vaccine using these methods.

Results

We found that the bias in the CLR analysis from previous studies was due to sparse data bias. It can be controlled by the bias-reduction method for CLR or by increasing the number of cases and/or controls. ULR with adjustment for time in quintiles usually gave results highly comparable to CLR, despite breaking the matches. Further adjustment for residual time trends was needed in the case of time-varying effects. ULR with adjustment for matched sets tended to perform poorly despite bias reduction.

Conclusions

Studies using incidence density sampling may be analysed by either ULR with adjustment for time or CLR, possibly with bias reduction.

Estimation of age effect with change-points on survival of cancer patients

There is a global trend that the average onset age of many human complex diseases is decreasing, and the age of cancer patients becomes more spread out. The age effect on survival is nonlinear in practice and may have one or more important change-points at which the trend of the effect can be very different before and after these threshold ages. Identification of these change-points allows clinical researchers to understand the biologic basis for the complex relation between age and prognosis for optimal prognostic decision. This paper considers estimation of the potentially nonlinear age effect for general partly linear survival models to ensure a valid statistical inference on the treatment effect. A simple and efficient sieve maximum likelihood estimation method that can be implemented easily using standard statistical software is proposed. A data-driven adaptive algorithm to determine the optimal location and the number of knots for the identification of the change-points is suggested. Simulation studies are performed to study the performance of the proposed method. For illustration purpose, the method is applied to a breast cancer data set from the public domain to investigate the effect of onset age on the disease-free survival of the patients. The results revealed that the risk is highest among young patients and young postmenopausal patients, probably because of a change in hormonal environment during a certain phase of menopause.

Semiparametric estimation of time-varying intervention effects using recurrent event data

We consider the estimation of the optimal interval between doses for interventions such as malaria chemoprevention and vaccine booster doses that are applied intermittently in infectious disease control. A flexible exponential-like function to model the time-varying intervention effect in the framework of Andersen-Gill model for recurrent event time data is considered. The partial likelihood estimation approach is adopted, and a large scale simulation study is carried out to evaluate the performance of the proposed method. A simple guideline for the choice of the optimal interval between successive doses is proposed. The methodology is illustrated with the analysis of data from a malaria chemoprevention trial. Copyright © 2017 John Wiley & Sons, Ltd.

Bayesian Analysis of Clustered Interval-censored Data

The recording of multiple interval-censored failure times is common in dental research. Modeling multilevel data has been a difficult task. This paper aims to use the Bayesian approach to analyze a set of multilevel clustered interval-censored data from a clinical study to investigate the effectiveness of silver diamine fluoride and sodium fluoride varnish in arresting active dentin caries in Chinese pre-school children. The time to arrest dentin caries on a surface was measured. A three-level random-effects Weibull regression model was used. Analysis was performed with WinBUGS. Results revealed a strong positive correlation (0.596) among the caries lesions’ arrest times on different surfaces from the same child. The software WinBUGS made the above complicated estimation simple. In conclusion, the annual application of silver diamine fluoride on caries lesions, and caries removal before the application, were found to shorten the arrest time.

Sample size determination for fold-increase endpoints defined by paired interval-censored data

Medical studies often define binary end-points by comparing the ratio of a pair of measurements at baseline and end-of-study to a clinically meaningful cut-off. For example, vaccine trials may define a response as at least a four-fold increase in antibody titers from baseline to end-of-study. Accordingly, sample size is determined based on comparisons of proportions. Since the pair of measurements is quantitative, modeling the bivariate cumulative distribution function to estimate the proportion gives more precise results than using dichotomization of data. This is known as the distributional approach to the analysis of proportions. However, this can be complicated by interval-censoring. For example, due to the nature of some laboratory measurement methods, antibody titers are interval-censored. We derive a sample size formula based on the distributional approach for paired interval-censored data. We compare the sample size requirement in detecting an intervention effect using the distributional approach to a conventional approach of dichotomization. Some practical guidance on applying the sample size formula is given.

Evaluation of psychometric properties and differential item functioning of 8-item Child Perceptions Questionnaires using item response theory

Background

Four-factor structure of the two 8-item short forms of Child Perceptions Questionnaire CPQ_11–14 (RSF:8 and ISF:8) has been confirmed. However, the sum scores are typically reported in practice as a proxy of Oral health-related Quality of Life (OHRQoL), which implied a unidimensional structure. This study first assessed the unidimensionality of 8-item short forms of CPQ_11–14. Item response theory (IRT) was employed to offer an alternative and complementary approach of validation and to overcome the limitations of classical test theory assumptions.

Methods

A random sample of 649 12-year-old school children in Hong Kong was analyzed. Unidimensionality of the scale was tested by confirmatory factor analysis (CFA), principle component analysis (PCA) and local dependency (LD) statistic. Graded response model was fitted to the data. Contribution of each item to the scale was assessed by item information function (IIF). Reliability of the scale was assessed by test information function (TIF). Differential item functioning (DIF) across gender was identified by Wald test and expected score functions.

Results

Both CPQ_11–14 RSF:8 and ISF:8 did not deviate much from the unidimensionality assumption. Results from CFA indicated acceptable fit of the one-factor model. PCA indicated that the first principle component explained >30 % of the total variation with high factor loadings for both RSF:8 and ISF:8. Almost all LD statistic <10 indicated the absence of local dependency. Flat and low IIFs were observed in the oral symptoms items suggesting little contribution of information to the scale and item removal caused little practical impact. Comparing the TIFs, RSF:8 showed slightly better information than ISF:8. In addition to oral symptoms items, the item “Concerned with what other people think” demonstrated a uniform DIF (p < 0.001). The expected score functions were not much different between boys and girls.

Conclusions

Items related to oral symptoms were not informative to OHRQoL and deletion of these items is suggested. The impact of DIF across gender on the overall score was minimal. CPQ_11–14 RSF:8 performed slightly better than ISF:8 in measurement precision. The 6-item short forms suggested by IRT validation should be further investigated to ensure their robustness, responsiveness and discriminative performance.

Estimation of intervention effect using paired interval-censored data with clumping below lower detection limit

Outcome variables that are semicontinuous with clumping at zero are commonly seen in biomedical research. In addition, the outcome measurement is sometimes subject to interval censoring and a lower detection limit (LDL). This gives rise to interval-censored observations with clumping below the LDL. Level of antibody against influenza virus measured by the hemagglutination inhibition assay is an example. The interval censoring is due to the assay's technical procedure. The clumping below LDL is likely a result of the lack of prior exposure in some individuals such that they either have zero level of antibodies or do not have detectable level of antibodies. Given a pair of such measurements from the same subject at two time points, a binary 'fold-increase' endpoint can be defined according to the ratio of these two measurements, as it often is in vaccine clinical trials. The intervention effect or vaccine immunogenicity can be assessed by comparing the binary endpoint between groups of subjects given different vaccines or placebos. We introduce a two-part random effects model for modeling the paired interval-censored data with clumping below the LDL. Based on the estimated model parameters, we propose to use Monte Carlo approximation for estimation of the 'fold-increase' endpoint and the intervention effect. Bootstrapping is used for variance estimation. The performance of the proposed method is demonstrated by simulation. We analyze antibody data from an influenza vaccine trial for illustration.

Osteodesis for hallux valgus correction: is it effective?

BACKGROUND

Although the etiology of hallux valgus is contested, in some patients it may be failure of the stabilizing soft tissue structures around the first ray of the foot. Because there is lack of effective soft tissue techniques, osteotomies have become the mainstream surgical approach to compensate for the underlying soft tissue deficiency; osteodesis, a soft tissue nonosteotomy technique, may be a third alternative, but its efficacy is unknown.

QUESTIONS/PURPOSES

We asked: (1) Can an osteodesis, a distal soft tissue technique, correct hallux valgus satisfactorily in terms of deformity correction and improvement in American Orthopaedic Foot and Ankle Society (AOFAS) score? (2) Is the effectiveness of an osteodesis affected by the patient's age or deformity severity? (3) What complications are associated with this procedure?

METHODS

Between February and October 2010, we performed 126 operations to correct hallux valgus, of which 126 (100%) were osteodeses. Sixty-one patients (110 procedures) (87% of the total number of hallux valgus procedures) were available for followup at a minimum of 12 months (mean, 23 months; range, 12-38 months). This group formed our study cohort. During the study period, the general indications for this approach included failed conservative measures for pain relief and metatarsophalangeal angle greater than 20° or intermetatarsal angle greater than 9°. Intermetatarsal cerclage sutures were used to realign the first metatarsal and postoperative fibrosis was induced surgically between the first and second metatarsals to maintain its alignment. The radiologic first intermetatarsal angle, metatarsophalangeal angle, and medial sesamoid position were measured by Hardy and Clapham's methods for deformity and correction evaluation. Clinical results were assessed by the AOFAS score.

RESULTS

The intermetatarsal angle was improved from a preoperative mean of 14° to 7° (p<0.001; Cohen's d=1.8) at followup, the metatarsophalangeal angle from 31° to 18° (p<0.001; Cohen's d=3.1), the medial sesamoid position from position 6 to 3 (p<0.001; Cohen's d=2.4), and AOFAS hallux score from 68 to 96 points (p<0.001). Neither patient age nor deformity severity affected the effectiveness of the osteodesis in correcting all three radiologic parameters; however, the deformities treated in this series generally were mild to moderate (mean intermetatarsal angle, 14°; range, 9°-22°). There were six stress fractures of the second metatarsal (5%), five temporary metatarsophalangeal joint medial subluxations all resolved in one month by the taping-reduction method without surgery, and six metatarsophalangeal joints with reduced dorsiflexion less than 60°.

CONCLUSIONS

The osteodesis is a soft tissue nonosteotomy technique, and provided adequate deformity correction and improvement in AOFAS scores for patients with mild to moderate hallux valgus deformities, although a small number of the patients had postoperative stress fractures of the second ray develop. Future prospective studies should compare this technique with osteotomy techniques in terms of effectiveness of the correction, restoration of hallux function, complications, and long-term recurrence.

LEVEL OF EVIDENCE

Level IV, therapeutic study. See the Instructions for Authors for a complete description of levels of evidence.

A simple and powerful method for the estimation of intervention effects on serological endpoints using paired interval-censored data

Clinical trials often use a binary "fold increase" endpoint defined according to the ratio of interval-censored measurement at end-of-study to that at baseline. We propose a simple yet principled analytic approach based on the linear mixed-effects model for interval-censored data for the analysis of such paired measurements. Having estimated the model parameters, the risk ratio can be estimated by explicit composite estimand and the variance is estimated using the delta method. The estimation can be implemented using the existing procedures in popular statistical software. We use antibody data from the Chloroquine for Influenza Prevention Trial for illustration.

Western mental health training for traditional Chinese medicine practitioners

OBJECTIVE

To investigate the impact of a Western mental health training course for Traditional Chinese Medicine (TCM) practitioners.

METHOD

  A combined qualitative and quantitative approach was applied to examine the changes in the TCM practitioners' clinical practice characteristics and attitudes. Focus groups and structured questionnaire surveys were conducted to compare their responses before and after the Course.

RESULTS

After a 10-week training course conducted by psychiatrists and family physicians, there were significant changes in confidence of the TCM practitioners for diagnosis (33% being confident before the Course vs. 76% after the Course) and management (24% vs. 55%) of common mental health problems. The causal effects of better classifications to recognition of mental health problems were explained by the qualitative responses. Proportion of TCM practitioners being confident of referring mental health patients to other healthcare professionals doubled from 25% to 50% after the Course. Nonetheless, there was no significant change in percentage of these patients being recommended to Western doctors owing to a lack of formal referral channel.

CONCLUSIONS

Western mental health training for TCM practitioners has positive impact on their clinical practice. However, the practical barriers in making referrals highlight the need of closer collaboration between conventional and traditional medicine.

Antibiotic use: do parents act differently for their children?

BACKGROUND

Many children in the community take antibiotics inappropriately. Previous studies comparing parents with other adults suggest that parents are more judicious with antibiotics for their children. This study aims to explore the difference between parents' use of antibiotics for themselves and for their children.

METHODS

The study adopted a combined qualitative and quantitative approach. Eight focus groups were conducted with 56 participants purposively recruited from community centres and of different socio-economic strata. The qualitative data collected were used to construct a questionnaire for the telephone survey, which recruited 2471 adults randomly selected from the local household directory, of whom 547 had ever brought their children or grand children for medical consultation.

RESULTS

Both the qualitative and quantitative approaches showed that parents were more cautious with antibiotics for children than for themselves. The main reason was their concern of side effects. Fever was the most important drive for their desire of antibiotics for children. The misconception of antibiotics' effectiveness for sore throat was another determinant of the desire. These attitudes and behaviour were not affected by the respondents' sex, age, education or household income.

CONCLUSION

On the whole, parents did to their children what they would do for themselves, but to a lesser extent. Parents' better knowledge and attitudes will lead to more appropriate use of antibiotics for their children.

Modeling zero-inflated count data using a covariate-dependent random effect model

In various medical related researches, excessive zeros, which make the standard Poisson regression model inadequate, often exist in count data. We proposed a covariate-dependent random effect model to accommodate the excess zeros and the heterogeneity in the population simultaneously. This work is motivated by a data set from a survey on the dental health status of Hong Kong preschool children where the response variable is the number of decayed, missing, or filled teeth. The random effect has a sound biological interpretation as the overall oral health status or other personal qualities of an individual child that is unobserved and unable to be quantified easily. The overall measure of oral health status, responsible for accommodating the excessive zeros and also the heterogeneity among the children, is covariate dependent. This covariate-dependent random effect model allows one to distinguish whether a potential covariate has an effect on the conceived overall oral health condition of the children, that is, the random effect, or has a direct effect on the magnitude of the counts, or both. We proposed a multiple imputation approach for estimation of the parameters. We discussed the choice of the imputation size. We evaluated the performance of the proposed estimation method through simulation studies, and we applied the model and method to the dental data.

What do primary care doctors get out of a year-long postgraduate course in community psychological medicine?

OBJECTIVE

There are increasing expectations on primary care doctors to care for patients with common mental health problems. This study examines the outcomes of a postgraduate training course in psychological medicine for primary care doctors.

METHODS

A questionnaire developed by the research team was sent to the Course graduates (year 2003-2007). A retrospective design was adopted to compare their clinical practice characteristics before and after the Course. Differences in the ratings by the respondents before and after the Course were analyzed using the nonparametric Wilcoxon signed rank test.

RESULTS

Sixty-nine graduates replied with a response rate of 58.5% (69/118). Most respondents were confident of diagnosing (96.9%) and managing (97.0%) common mental health problems after the Course, compared to 50.0% and 50.7%, respectively, before the Course. Most graduates had modified their approach, increased their attention and empathy to patients with mental health problems. The percentage of respondents having enough time to treat these patients had increased from 55.8% to 72.1%. The median number of patients with mental health problems seen per week was in the range of 3-6 before, and had increased to the range of 7-10 after the Course. The proportion of respondents being confident of making appropriate referrals had increased from 72.8% to 97.0%, while the number of referrals to psychiatrists had dropped significantly.

CONCLUSIONS

The Course is effective in improving graduates' confidence, attitude, and skills in treating patients with common mental health problems. There are significant increases in the number of mental health patients handled, increased confidence in making referrals to psychiatrists, and decreased percentage of patients being referred.

What are the learning outcomes of a short postgraduate training course in dermatology for primary care doctors?

BACKGROUND

There are increasing expectations on primary care doctors to shoulder a bigger share of care for patients with common dermatological problems in the community. This study examined the learning outcomes of a short postgraduate course in dermatology for primary care doctors.

METHODS

A self-reported questionnaire developed by the research team was sent to the Course graduates. A retrospective design was adopted to compare their clinical practice characteristics before and after the Course. Differences in the ratings were analysed using the nonparametric Wilcoxon signed rank test to evaluate the effectiveness of the Course in various aspects.

RESULTS

Sixty-nine graduates replied with a response rate of 42.9% (69/161). Most were confident of diagnosing (91.2%) and managing (88.4%) common dermatological problems after the Course, compared to 61.8% and 58.0% respectively before the Course. Most had also modified their approach and increased their attention to patients with dermatological problems. The number of patients with dermatological problems seen by the graduates per day showed significant increase after the Course, while the average percentage of referrals to dermatologists dropped from 31.9% to 23.5%. The proportion of graduates interested in following up patients with chronic dermatological problems increased from 60.3% to 77.9%.

CONCLUSIONS

Graduates of the Course reported improved confidence, attitudes and skills in treating common dermatological problems. They also reported to handle more patients with common dermatological problems in their practice and refer fewer patients.

Development of multistage distillation in a microfluidic chip

Although there has been a lot of work on the development of microchemical processing systems such as micro-reactors and micro-sensors, little attention has been paid to micro-separation units, and in particular, microscale distillation. In this paper, various silicon-glass microscale distillation chips with different channel configurations were fabricated and tested. A temperature gradient was setup across the chip by heating and cooling the two ends. The feed was located at the middle of the microchannel. Arrays of micropillars were incorporated in order to guide the liquid flow. It was found that the separation performance was promoted by increasing the length of the microchannel. However, this created an imbalance of the liquid flows at the two sides of the microchannel and caused flooding. This hydrodynamic limitation was addressed by incorporating micropillars on both sides of the channel. The most efficient microdistillation chip consisted of a microchannel with 600 microns width and 40 cm length. Experimental results showed high efficiency for the separation of a 50 mol% acetone-water mixture when the heating and cooling temperature were 95 °C and 42 °C respectively. The concentrations of acetone were 3 mol% in the bottom stream and 95 mol% in the distillate, which was equivalent to at least 4 equilibrium stages at total reflux conditions. Furthermore, a 50 mol% methanol-toluene mixture was separated into nearly pure toluene in the bottom stream and 75 mol% methanol in the distillate. The performance of the microdistillation unit was reproducible in repeated tests.

Family medicine training in Hong Kong: similarities and differences between family and non-family doctors

OBJECTIVE

To study the local medical profession's opinions on the training requirements for the specialty of family medicine. This was to serve as a reference for future planning of the health care system.

DESIGN

Cross-sectional study.

PARTICIPANTS AND SETTING

All registered doctors in Hong Kong.

MAIN OUTCOME MEASURES

Doctors' ratings on the importance of vocational training, professional assessment, job nature, and experience to become suitably qualified as a family doctor, and their opinions on the length of necessary vocational training.

RESULTS

A total of 2310 doctors (23% of doctors in the local register) responded. Professional assessment was mostly agreed as a qualification, followed by vocational training, clinical experience, and job nature. Over 70% agreed on a training period of 4 years or less. Non-family doctors were more likely to opt for professional assessment as the qualification and also opt for a longer training period.

CONCLUSION

Vocational training was considered important as a qualification for the specialty of family medicine. The length of training was mostly agreed to be 4 years or less, not the 6 years currently required by the Hong Kong Academy of Medicine. The vocational training programme for family medicine might require re-examination.

Introducing family medicine in a pluralistic health care system: how patients and doctors see it

BACKGROUND

The health care systems in many countries are focused on specialist care. In those countries that have recently changed to a primary care-based system, some doctors and patients were dissatisfied with the change.

OBJECTIVE

To explore the opinions of the general public and the doctors on the change to a family medicine (FM)-based health care system.

METHODS

Qualitative study with focus groups of doctors working in different practice settings. Quantitative study with questionnaires sent to all doctors registered in Hong Kong and a telephone survey targeting the general public aged ≥18.

RESULTS

Doctors in the focus groups generally supported a FM-based health care system. They were concerned that there were not enough family doctors for such a system and the patients' current free choice of any doctor for primary care would impede its success. Thousand six hundred and forty-seven adults took part in the telephone survey (response rate 67.6%) and 2310 doctors (22.8%) responded to the questionnaire. Nearly 95% of the general public respondents agreed to the FM system though only 66.3% of them had ever heard of the term family doctor. About 65% of the doctors supported this system but only 33% agreed that the system would work. The specialist-doctors were less supportive of mandatory referral than the non-specialists, while the public was equally divided on this issue.

CONCLUSIONS

The public accepts the FM-based system but needs education on the benefits of primary health care. Direct access to the specialist would be the greatest barrier. Government involvements are essential for the reform.

Analysis of multilevel grouped survival data with time-varying regression coefficients

Correlated or multilevel grouped survival data are common in medical and dental research. Two common approaches to analyze such data are the marginal and the random-effects approaches. Models and methods in the literature generally assume that the treatment effect is constant over time. A researcher may be interested in studying whether the treatment effects in a clinical trial vary over time, say fade out gradually. This is of particular clinical value when studying the long-term effect of a treatment. This paper proposed to extend the random effects grouped proportional hazards models by incorporating the possibly time-varying covariate effects into the model in terms of a state-space formulation. The proposed model is very flexible and the estimation can be performed using the MCMC approach with non-informative priors in the Bayesian framework. The method is applied to a data set from a prospective clinical trial investigating the effectiveness of silver diamine fluoride (SDF) and sodium fluoride (NaF) varnish in arresting active dentin caries in the Chinese preschool children. It is shown that the treatment groups with caries removal prior to the topical fluoride applications are most effective in shortening the arrest times in the first 6-month interval, but their effects fade out rapidly since then. The effects of treatment groups without caries removal prior to topical fluoride application drop at a very slow rate and can be considered as more or less constant over time. The applications of SDF solution is found to be more effective than the applications of NaF vanish.

A simple approach to the estimation of incidence rate difference

The incidence rate difference (IRD) is a parameter of interest in many medical studies. For example, in vaccine studies, it is interpreted as the vaccine-attributable reduction in disease incidence. This is an important parameter, because it shows the public health impact of an intervention. The IRD is difficult to estimate for various reasons, especially when there are quantitative covariates or the duration of follow-up is variable. In this paper, the authors propose an approach based on weighted least-squares regression for estimating the IRD. It is very easy to implement because it boils down to performing ordinary least-squares regression analysis of transformed variables. Furthermore, if the outcome events are repeatable, the authors propose that data on all events be analyzed instead of first events only. Four versions of the Huber-White robust standard error are considered for statistical inference. Simulation studies are used to examine the performance of the proposed method. In a variety of scenarios simulated, the method provides an unbiased estimate for the IRD, and the empirical coverage proportion of the 95% confidence interval is very close to the nominal level. The method is illustrated with data from a vaccine trial carried out in the Gambia in 2001-2004.

Evaluation of the learning outcomes of a year-long postgraduate training course in community geriatrics for primary care doctors

There are increasing expectations on primary care doctors to shoulder a bigger share of care for patients with common geriatric problems in the community. This study aims to examine the outcomes of a postgraduate training course in geriatrics for primary care doctors. A questionnaire developed by the research team was sent to the course graduates (years 2001-2007). Ninety-eight replies were received with a response rate of 52.4% (98/187). Difference in the ratings by the respondents before and after taking the course was analyzed using the nonparametric Wilcoxon signed rank test. Most respondents felt more rewarding and had participated more in geriatric care, and the majority had improvement in their communication skills with elderly patients after taking the course. Moreover, the graduates are more confident in diagnosing and managing common geriatric problems, and deciding to which specialty to refer the elderly patients. Of the referrals, there was a significant increase to private geriatricians and a significant reduction to other specialists. The average number of elderly patients seen per day had also increased. However, little change was observed about making nursing home visits, the frequency of which remained low. Many graduates expressed difficulties in conducting nursing home visits.

Psychological well-being of interns in Hong Kong: what causes them stress and what helps them

BACKGROUND

Many doctors experience psychological ill health. Interns are known to be particularly vulnerable.

AIM

To examine the level of depression, anxiety and stress in interns in Hong Kong, as well as the causes and how they cope.

METHODS

A questionnaire was designed based on the themes identified in three focus groups of medical graduates of Year 2004 of the University of Hong Kong. The 21-item Depression, Anxiety and Stress Scale (DASS 21) was also administered. All 155 graduates of the same year were invited to participate with a response rate of 63%.

RESULTS

Percentages of respondents with abnormal levels of depression, anxiety and stress were 35.8%, 35.4% and 29.2%, respectively. Frequent calls during night shift, long working hours and heavy workload constituted the most significant stressors. Factor analysis of the stressors showed that seven factors could explain 68% of the total variance: multidisciplinary team working issues, clinical difficulties, job seeking and employment, workload issues, ethical and interpersonal issues, adjustment to job rotation and performance appraisal. Holidays, peers and sleep offered the most significant relief.

CONCLUSION

Interns experience considerable depression, anxiety and stress. The source of stress is multi-faceted, but workload is the most significant stressor. Peer support groups may relief stress.

Iron supplement in pregnancy and development of gestational diabetes--a randomised placebo-controlled trial

OBJECTIVE

To test the hypothesis that iron supplement from early pregnancy would increase the risk of gestational diabetes mellitus (GDM).

DESIGN

Randomised placebo-controlled trial.

SETTING

A university teaching hospital in Hong Kong.

POPULATION

One thousand one hundred sixty-four women with singleton pregnancy at less than 16 weeks of gestation with haemoglobin (Hb) level between 8 and 14 g/dl and no pre-existing diabetes or haemoglobinopathies.

METHODS

Women were randomly allocated to receive 60 mg of iron supplement daily (n= 565) or placebo (n= 599). Oral glucose tolerance tests (OGTTs) were performed at 28 and 36 weeks. Women were followed up until delivery.

OUTCOME MEASURES

The primary outcome was development of GDM at 28 weeks. The secondary outcomes were 2-hour post-OGTT glucose levels, development of GDM at 36 weeks and delivery and infant outcomes.

RESULTS

There was no significant difference in the incidence of GDM in the iron supplement and placebo groups at 28 weeks (OR: 1.04, 95% confidence interval [CI]: 0.7-1.53 at 90% power) or 36 weeks. Maternal Hb and ferritin levels were higher in the iron supplement group at delivery (P < 0.001 and P= 0.003, respectively). Elective caesarean section rate was lower in the iron supplement group (OR: 0.58, 95% CI: 0.37-0.89). Infant birthweight was heavier (P= 0.001), and there were fewer small-for-gestational-age babies in the iron supplement group (OR: 0.46, 95% CI: 0.24-0.85).

CONCLUSION

Iron supplement from early pregnancy does not increase the risk of GDM. It may have benefits in terms of pregnancy outcomes.

Three estimates of the association between linear growth failure and cognitive ability

OBJECTIVES

To compare three estimators of association between growth stunting as measured by height-for-age Z-score and cognitive ability in children, and to examine the extent statistical adjustment for covariates is useful for removing confounding due to socio-economic status.

METHODS

Three estimators, namely random-effects, within- and between-cluster estimators, for panel data were used to estimate the association in a survey of 1105 pairs of siblings who were assessed for anthropometry and cognition. Furthermore, a 'combined' model was formulated to simultaneously provide the within- and between-cluster estimates.

RESULTS

Random-effects and between-cluster estimators showed strong association between linear growth and cognitive ability, even after adjustment for a range of socio-economic variables. In contrast, the within-cluster estimator showed a much more modest association: For every increase of one Z-score in linear growth, cognitive ability increased by about 0.08 standard deviation (P < 0.001). The combined model verified that the between-cluster estimate was significantly larger than the within-cluster estimate (P = 0.004).

CONCLUSION

Residual confounding by socio-economic situations may explain a substantial proportion of the observed association between linear growth and cognition in studies that attempt to control the confounding by means of multivariable regression analysis. The within-cluster estimator provides more convincing and modest results about the strength of association.

A test for constant fatality rate of an emerging epidemic: with applications to severe acute respiratory syndrome in Hong Kong and Beijing

The etiology, pathogenesis, and prognosis for a newly emerging disease are generally unknown to clinicians. Effective interventions and treatments at the earliest possible times are warranted to suppress the fatality of the disease to a minimum, and inappropriate treatments should be abolished. In this situation, the ability to extract most information out of the data available is critical so that important decisions can be made. Ineffectiveness of the treatment can be reflected by a constant fatality over time while effective treatment normally leads to a decreasing fatality rate. A statistical test for constant fatality over time is proposed in this article. The proposed statistic is shown to converge to a Brownian motion asymptotically under the null hypothesis. With the special features of the Brownian motion, we are able to analyze the first passage time distribution based on a sequential tests approach. This allows the null hypothesis of constant fatality rate to be rejected at the earliest possible time when adequate statistical evidence accumulates. Simulation studies show that the performance of the proposed test is good and it is extremely sensitive in picking up decreasing fatality rate. The proposed test is applied to the severe acute respiratory syndrome data in Hong Kong and Beijing.