Dataset Information

Integrated analysis of incidence, progression, regression and disappearance probabilities.

ABSTRACT:

Background

Age-related maculopathy (ARM) is a leading cause of vision loss in people aged 65 or older. ARM is distinctive in that it is a disease which can transition through incidence, progression, regression and disappearance. The purpose of this study is to develop methodologies for studying the relationship of risk factors with different transition probabilities.

Methods

Our framework for studying this relationship includes two different analytical approaches. In the first approach, one can define, model and estimate the relationship between each transition probability and risk factors separately. This approach is similar to constraining a population to a certain disease status at the baseline, and then analyzing the probability of the constrained population to develop a different status. While this approach is intuitive, one risks losing available information while at the same time running into the problem of insufficient sample size. The second approach specifies a transition model for analyzing such a disease. This model provides the conditional probability of a current disease status based upon a previous status, and can therefore jointly analyze all transition probabilities. Throughout the paper, an analysis to determine the birth cohort effect on ARM is used as an illustration.

Results and conclusion

This study has found parallel separate and joint analyses to be more enlightening than any analysis in isolation. By implementing both approaches, one can obtain more reliable and more efficient results.

SUBMITTER: Huang GH

PROVIDER: S-EPMC2459200 | biostudies-literature | 2008 Jun

REPOSITORIES: biostudies-literature

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Publications

Integrated analysis of incidence, progression, regression and disappearance probabilities.

Huang Guan-Hua GH

BMC medical research methodology 20080625

<h4>Background</h4>Age-related maculopathy (ARM) is a leading cause of vision loss in people aged 65 or older. ARM is distinctive in that it is a disease which can transition through incidence, progression, regression and disappearance. The purpose of this study is to develop methodologies for studying the relationship of risk factors with different transition probabilities.<h4>Methods</h4>Our framework for studying this relationship includes two different analytical approaches. In the first app ...[more]

PMID: 18577235

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Project description:Cancer is one of the leading causes of death worldwide and its incidence is expected to increase in the future. In Panama, cancer is also one of the leading causes of death. In 1964, a nationwide cancer registry was started and it was restructured and improved in 2012. The aim of this study is to utilize Joinpoint regression analysis to study the trends of the incidence and mortality of cancer in Panama in the last decade. Cancer mortality was estimated from the Panamanian National Institute of Census and Statistics Registry for the period 2001 to 2011. Cancer incidence was estimated from the Panamanian National Cancer Registry for the period 2000 to 2009. The Joinpoint Regression Analysis program, version 4.0.4, was used to calculate trends by age-adjusted incidence and mortality rates for selected cancers. Overall, the trend of age-adjusted cancer mortality in Panama has declined over the last 10 years (-1.12% per year). The cancers for which there was a significant increase in the trend of mortality were female breast cancer and ovarian cancer; while the highest increases in incidence were shown for breast cancer, liver cancer, and prostate cancer. Significant decrease in the trend of mortality was evidenced for the following: prostate cancer, lung and bronchus cancer, and cervical cancer; with respect to incidence, only oral and pharynx cancer in both sexes had a significant decrease. Some cancers showed no significant trends in incidence or mortality. This study reveals contrasting trends in cancer incidence and mortality in Panama in the last decade. Although Panama is considered an upper middle income nation, this study demonstrates that some cancer mortality trends, like the ones seen in cervical and lung cancer, behave similarly to the ones seen in high income countries. In contrast, other types, like breast cancer, follow a pattern seen in countries undergoing a transition to a developed economy with its associated lifestyle, nutrition, and body weight changes.

Project description:IntroductionMany studies have been conducted worldwide to estimate herpes zoster (HZ) incidence rates. We synthesized studies of HZ incidence rates in the general population using meta-analysis models.MethodsA random effects meta-analysis was conducted to estimate HZ incidence from a published worldwide systematic literature review (SLR) including only individuals aged 50 years and older. Meta-regression was used to explore whether variability in incidence rates could be explained by a combination of study-specific characteristics including age, gender, continent and year of study data. The impact of adding additional covariates-case detection method (general practitioner surveillance, healthcare database, sentinel network, etc.), case definition (medical record-based, self-reported), study design (retrospective passive surveillance, retrospective active surveillance, etc.), incidence type (cumulative incidence/1000 persons or incidence rate/1000 person-years), patient type (outpatients or in- and out-patients) and latitude to the base model-was also assessed.ResultsSixty-one records from 59 studies were included in the analysis: 25, 20, 11 and 5 from Europe, North America, Asia and Oceania, respectively. There was variation in study methodology and outcomes. Heterogeneity of incidence rates was greatest among studies conducted in Asia. Meta-analysis showed that incidence increased with age, was lower in males compared to females, tended to be lower in Europe and North America compared to Asia and Oceania and increased with year of study data. The data-driven meta-regression model included continent, year of study data, gender, age and an age × gender interaction term. The difference in incidence between males and females was greater in younger ages (e.g., 50-59) compared to older age groups (e.g., 80+). None of the additional covariates contributed significantly to the model.ConclusionIncidence rates were shown to vary by age, gender, continent and year of study data.

Dataset Information

Integrated analysis of incidence, progression, regression and disappearance probabilities.

Background

Methods

Results and conclusion

Publications

Integrated analysis of incidence, progression, regression and disappearance probabilities.

Similar Datasets

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