Socio-demographic and clinical profile of admissions to community hospitals in Singapore from 1996 to 2005: a descriptive study

<p><b>INTRODUCTION</b>Little data is available on community hospital admissions. We examined the differences between community hospitals and the annual trends in sociodemographic characteristics of all patient admissions in Singaporean community hospitals over a 10- year period from 1996 to 2005.</p><p><b>MATERIALS AND METHODS</b>Data were manually extracted from medical records of 4 community hospitals existent in Singapore from 1996 to 2005. Nineteen thousand and three hundred and sixty patient records were examined. Chisquare test was used for univariate analysis of categorical variables by type of community hospitals. For annual trends, test for linear by linear association was used. ANOVA was used to generate beta coefficients for continuous variables.</p><p><b>RESULTS</b>Mean age of all patient admissions has increased from 72.8 years in 1996 to 74.8 years in 2005. The majority was Chinese (88.4%), and female (58.1%) and admissions were mainly for rehabilitation (88.0%). Almost one third had foreign domestic workers as primary caregivers and most (73.5%) were discharged to their own home. There were significant differences in socio-demographic profile of admissions between hospitals with one hospital having more patients with poor social support. Over the 10-year period, the geometric mean length of stay decreased from 29.7 days (95% CI, 6.4 to 138.0) to 26.7 days (95% CI, 7.5 to 94.2), and both mean admission and discharge Barthel Index scores increased from 41.0 (SD = 24.9) and 51.8 (SD = 30.0), respectively in 1996 to 48.4 (SD = 24.5) and 64.2 (SD = 27.3) respectively in 2005.</p><p><b>CONCLUSION</b>There are significant differences in socio-demographic characteristics and clinical profile of admissions between various community hospitals and across time. Understanding these differences and trends in admission profiles may help in projecting future healthcare service needs.</p>

Corrigendum / 예방의학회지

The authors regret that they incorrectly cited the name of one of the authors and the contact number of the corresponding author in the original publication. The name of the first author should have read: Nasheen Naidoo. The correct contact number of the corresponding author, Kee Seng Chia, is (65)6516-4971.

Incidence, mortality and five-year relative survival ratio of prostate cancer among Chinese residents in Singapore from 1968 to 2002 by metastatic staging

<p><b>INTRODUCTION</b>This paper examines the incidence, mortality and survival patterns among all Chinese residents with prostate cancer reported to the Singapore Cancer Registry in Singapore from 1968 to 2002 by metastatic staging.</p><p><b>MATERIALS AND METHODS</b>This is a retrospective population-based study including all prostate cancer cases aged over 20 reported to the Singapore Cancer Registry (SCR) from 1968 to 2002 who are Singapore Chinese residents. Follow-up was ascertained by matching with the National Death Register until 2002. Metastatic status was obtained from the SCR. Age-standardised incidence and mortality rates, as well as the 5-year relative survival ratios (RSRs), were obtained for each 5-year period and grouped by metastatic stage. A weighted linear regression was performed on the log-transformed age-standardised incidence and mortality rates over the study period.</p><p><b>RESULTS</b>In the most recent period of 1998 to 2002, the age-standardised incidence and mortality rates (per 100,000) for prostate cancer among the Chinese were 30.9 (95% CI, 29.1 to 32.8) and 9.6 (95% CI, 8.6 to 10.7), respectively. The percentage increase in the age-standardised incidence and age-standardised mortality rates per year were 5.6% and 6.0%, respectively, for all Chinese Singapore residents. There was an improvement in the 5-year RSRs for Chinese diagnosed with non-metastatic cases from 51.3% in 1973 to 1977, to 76.1% in 1998 to 2002. However, the RSR remains poor (range, 11.1% to 49.7%) for Chinese diagnosed with metastatic prostate cancer.</p><p><b>CONCLUSIONS</b>Both age-standardised incidence and mortality rates for prostate cancer among Chinese Singapore residents are still on the rise especially since the 1990s. Since the 1990s, the improvement in RSRs was substantial for the Chinese non-metastatic cases.</p>

Trends in long-term cancer survival in Singapore: 1968-2002

<p><b>INTRODUCTION</b>The life expectancy of cancer patients has increased in recent decades due to better diagnostic and screening tools as well as better treatment modalities. Hence, it becomes increasingly important to study trends in long-term cancer patient survival in order to document that medical progress has conveyed benefit at the population level. In this paper, we assessed the long-term survival experience of all incident cancer patients in Singapore.</p><p><b>MATERIALS AND METHODS</b>The study population consisted of patients diagnosed with single primary invasive cancer from 1 January 1968 to 31 December 2002, and passively followed up to 31 December 2005. The data was derived from the Singapore Cancer Registry, which has been in existence since 1968. Relative survival via the period approach was used to provide a more up-to-date estimate by looking at recent cohorts of patients. Sex- and stage-specific survival was compared for each cancer.</p><p><b>RESULTS</b>The overall age-standardised 10-year relative survival ratios for the calendar years of 1998 to 2002 were 30.5% in males and 44.2% in females. A steady improvement in overall long-term cancer survival was observed over the study period. This upward trend in survival was observed in localised tumours and cancers with a favourable prognosis such as breast, cervical and colorectal cancers. In contrast, survival of cancers with poor prognosis such as lung, liver and pancreas remained low.</p><p><b>CONCLUSIONS</b>Although factors such as changes in diagnostic criteria could influence the trend in survival, we believed that the improvement in survival predominantly reflected real progress in cancer control in Singapore.</p>

A practical guide for multivariate analysis of dichotomous outcomes

A dichotomous (2-category) outcome variable is often encountered in biomedical research, and Multiple Logistic Regression is often deployed for the analysis of such data. As Logistic Regression estimates the Odds Ratio (OR) as an effect measure, it is only suitable for case-control studies. For cross-sectional and time-to-event studies, the Prevalence Ratio and Cumulative Incidence Ratio can be estimated and easily interpreted. The logistic regression will produce the OR which is difficult to interpret in these studies. In this report, we reviewed 3 alternative multivariate statistical models to replace Logistic Regression for the analysis of data from cross-sectional and time-to-event studies, viz, Modified Cox Proportional Hazard Regression Model, Log-Binomial Regression Model and Poisson Regression Model incorporating the Robust Sandwich Variance. Although none of the models is without flaws, we conclude the last model is the most viable. A numeric example is given to compare the statistical results obtained from all 4 models.

Discovering Gene-Environment Interactions in the Post-Genomic Era / 예방의학회지

In the more than 100 genome wide association studies (GWAS) conducted in the past 5 years, more than 250 genetic loci contributing to more than 40 common diseases and traits have been identified. Whilst many genes have been linked to a trait, both their individual and combined effects are small and unable to explain earlier estimates of heritability. Given the rapid changes in disease incidence that cannot be accounted for by changes in diagnostic practises, there is need to have well characterized exposure information in addition to genomic data for the study of gene-environment interactions. The case-control and cohort study designs are most suited for studying associations between risk factors and occurrence of an outcome. However, the case control study design is subject to several biases and hence the preferred choice of the prospective cohort study design in investigating gene-environment interactions. A major limitation of utilising the prospective cohort study design is the long duration of follow-up of participants to accumulate adequate outcome data. The GWAS paradigm is a timely reminder for traditional epidemiologists who often perform one- or few-at-a-time hypothesis-testing studies with the main hallmarks of GWAS being the agnostic approach and the massive dataset derived through large-scale international collaborations.