Scientific Productivity on Research in Ethical Issues over the Past Half Century: A JoinPoint Regression Analysis

Gastric cancer incidence trends in China and Japan from 1990 to 2019: Disentangling age-period-cohort patterns

BACKGROUND

Recent data have shown divergent trends in gastric cancer (GC) incidence between China and Japan; however, the cause for has not been explored.

METHODS

We retrieved GC incidence data from 1990 to 2019 from the Global Burden of Disease study, stratified by sex for both countries. We analyzed annual average percentage change (AAPC) via a joinpoint regression model and estimated the effects of age, period, and cohort via the age-period-cohort model.

RESULTS

The age-standardized incidence rate trends for GC decreased in both countries and both sexes, but the reduction was more pronounced in Japan because the AAPC for Japanese males (AAPC = -2.65%; 95% CI, -2.98 to -2.32) was eight times greater than that of Chinese males (AAPC = -0.30%; 95% CI, -0.5 to -0.09). The age and cohort effects on the trend are similar in both countries: the risk of GC incidence increased with age among the Chinese and the Japanese but was lower among younger birth cohorts. The two countries showed contrasting trends over the study period; although the risk of GC rapidly decreased for Japanese males and females, it increased by twofold among Chinese males.

CONCLUSIONS

The period effect is the main reason for the divergent trends in age-standardized incidence rate for GC in China and Japan. By comparing national cancer control programs in both countries, we concluded that countries with a high prevalence of GC, such as China, can learn from Japan's experience in controlling GC by actively conducting national population screening, which is expected to facilitate both prevention and treatment of GC.

LAY SUMMARY

More than one-half of all new gastric cancer (GC) worldwide occur in China and Japan, but the reasons for the different incidence trends have not been thoroughly analyzed. Analysis using the age-period-cohort model confirmed that the cohort effect was the main reason for the decline in age-standardized incidence rate (ASIR) for GC and that the period effect may be the main reason for the divergent trends in gastric cancer ASIR in China and Japan.

The Burden of Dengue in Children by Calculating Spatial Temperature: A Methodological Approach Using Remote Sensing Techniques

BACKGROUND

Dengue fever is one of the most important arboviral diseases. Surface temperature versus dengue burden in tropical environments can provide valuable information that can be adapted in future measurements to improve health policies.

METHODS

A methodological approach using Daymet-V3 provided estimates of daily weather parameters. A Python code developed by us extracted the median temperature from the urban regions of Colima State (207.3 km2) in Mexico. JointPoint regression models computed the mean temperature-adjusted average annual percentage of change (AAPC) in disability-adjusted life years (DALY) rates (per 100,000) due to dengue in Colima State among school-aged (5-14 years old) children.

RESULTS

Primary outcomes were average temperature in urban areas and cumulative dengue burden in DALYs in the school-aged population. A model from 1990 to 2017 medium surface temperature with DALY rates was performed. The increase in DALYs rate was 64% (95% CI, 44-87%), and it seemed to depend on the 2000-2009 estimates (AAPC = 185%, 95% CI 18-588).

CONCLUSION

From our knowledge, this is the first study to evaluate surface temperature and to model it through an extensive period with health economics calculations in a specific subset of the Latin-American endemic population for dengue epidemics.

The utility of joinpoint regression for estimating population parameters given changes in population structure

The method of joinpoint regression has been used in numerous domains to assess changes in time series data, including such things as cancer mortality rates, motor vehicle collision mortalities, and disease risk. To help improve estimation of population parameters for use in ecological risk assessment and management, we present a simulation and analysis to describe the utility of this method for the ecological domain. We demonstrate how joinpoint regression can accurately identify if the population structure changes based on time series of abundance, as well as identify when this change occurs. In addition, we compare and contrast population parameter estimates derived through joinpoint and surplus production methods to those derived from standard surplus production methods alone. When considering a change point at 32 years (out of a 64 year simulation), the joinpoint regression model was able, on average, to estimate a joinpoint time of 32.31 years with a variance of 6.82 and 95% confidence interval for the mean relative bias of (0.0085, 0.0112). The model was able to consistently estimate population parameters, with variance of these estimations decreasing as the change in these population parameters increased. We conclude that joinpoint regression be added to the list of methods employed by those who assess ecological risk to allow for a more accurate and complete understanding of population dynamics.

Participation of the hospitals in the Republic of Ireland in international research over more than a decade: a bibliometric analysis

BACKGROUND

This study provides an accurate awareness of the present situation of health research in Irish hospitals both public and private. We aimed to analyze factors that may influence it and provide recommendations for active steps to improve the current situation of Irish health research based on our findings.

METHODS

We performed a bibliometric analysis to assess qualitatively and quantitatively the publications from Ireland over a period between 2007 and 2018. We also investigated the associated variables with the quality of research. Furthermore, we conducted a Joinpoint analysis to see the trends in Irish research over these years.

RESULTS

From 12,828 included peer-reviewed articles, the average citation count per article was 19.98. Furthermore, we showed that a higher impact factor (IF) and institutions number, present per article, were significantly associated with more citations. Also, the publication count and the mean IF showed an increase over the years according to the Joinpoint analysis. Moreover, the oncology research had the highest output, followed by pediatrics, then neurology while the specialties with least publications were ear, nose, and throat (ENT), urology, plastic surgery, and dentistry. Additionally, cardiovascular, obstetrics and gynecology, oncology, pediatrics, pulmonology, dermatology, ophthalmology, dentistry, and radiology research showed an increased publication count trend in recent years. While anesthesiology, ENT, general surgery, gastroenterology and hepatology, infection and tropical medicine, nephrology, neurology, orthopedics, plastic surgery, and urology showed a decrease in the publications trend.

CONCLUSIONS

Our findings may serve as a useful approach to benchmark scientific output from hospitals and guide the future allocation of research spending.

Research trends in evidence-based medicine: a joinpoint regression analysis of more than 50 years of publication data

Background

Evidence-based medicine (EBM) has developed as the dominant paradigm of assessment of evidence that is used in clinical practice. Since its development, EBM has been applied to integrate the best available research into diagnosis and treatment with the purpose of improving patient care. In the EBM era, a hierarchy of evidence has been proposed, including various types of research methods, such as meta-analysis (MA), systematic review (SRV), randomized controlled trial (RCT), case report (CR), practice guideline (PGL), and so on. Although there are numerous studies examining the impact and importance of specific cases of EBM in clinical practice, there is a lack of research quantitatively measuring publication trends in the growth and development of EBM. Therefore, a bibliometric analysis was constructed to determine the scientific productivity of EBM research over decades.

Methods

NCBI PubMed database was used to search, retrieve and classify publications according to research method and year of publication. Joinpoint regression analysis was undertaken to analyze trends in research productivity and the prevalence of individual research methods.

Findings

Analysis indicates that MA and SRV, which are classified as the highest ranking of evidence in the EBM, accounted for a relatively small but auspicious number of publications. For most research methods, the annual percent change (APC) indicates a consistent increase in publication frequency. MA, SRV and RCT show the highest rate of publication growth in the past twenty years. Only controlled clinical trials (CCT) shows a non-significant reduction in publications over the past ten years.

Conclusions

Higher quality research methods, such as MA, SRV and RCT, are showing continuous publication growth, which suggests an acknowledgement of the value of these methods. This study provides the first quantitative assessment of research method publication trends in EBM.