Nurse prescribing in New Zealand-the difference in levels of prescribing explained.

This article discusses the three types of nurse prescriber currently registered in New Zealand (nurse practitioners, registered nurse prescribers (RNP) in primary health and specialty teams and registered nurse prescribers (RNPCH) in community health). It also provides an overview of the evolution of each group, as well as a summary of the current legislation, prescribing restrictions and models of supervision required for each type of prescriber.

Methodological issues in analyzing time trends in biologic fertility: protection bias.

One method of assessing biologic fertility is to measure time to pregnancy (TTP). Accidental pregnancies do not generate a valid TTP value and lead to nonrandom missing data if couples experiencing accidental pregnancies are more fertile than the general population. If factors affecting the rate of accidental pregnancies, such as availability of effective contraception and induced abortion, vary over time, then the result may be protection bias in the estimates of fertility time trends. Six European data sets were analyzed to investigate whether evidence of protection bias exists in TTP studies of fertility trends in Europe over the past 50 years. Couples experiencing accidental pregnancies tended to be more fertile than the general population. However, trends in accidental pregnancy rates were inconsistent across countries and were insufficient to produce substantial bias in fertility trends in simulated data. Where protection bias is suspected, the authors demonstrate use of 2 multiple imputation methods to generate realizations for the missing TTP values for accidental pregnancies. Simulation studies show that both methods successfully reduce or eliminate protection bias. The authors also demonstrate that standard sensitivity analyses for dealing with accidental pregnancies provide an upper bound on the extent of any bias.

Meta-analysis of studies of alcohol and breast cancer with consideration of the methodological issues.

OBJECTIVE: To give an up-to-date assessment of the association of alcohol with female breast cancer, addressing methodological issues and shortfalls in previous overviews. METHODS: Meta-analysis of studies (any language) providing original data on incidence of first primary breast cancer and alcohol. Two reviewers independently extracted data. Study quality assessed by objective criteria including degree of control for confounding; funnel plots examined for publication bias; meta-regression techniques to explore heterogeneity. Risks associated with drinking versus not drinking and dose-response not constrained through the origin estimated using random effects methods. RESULTS: Ninety-eight unique studies were included, involving 75,728 and 60,653 cases in drinker versus non-drinker and dose-response analyses, respectively. Findings were robust to study design and analytic approaches in the meta-analyses. For studies judged high quality, controlled for appropriate confounders, excess risk associated with alcohol drinking was 22% (95% CI: 9-37%); each additional 10 g ethanol/day was associated with risk higher by 10% (95% CI: 5-15%). There was no evidence of publication bias. Risk did not differ significantly by beverage type or menopausal status. Estimated population attributable risks were 1.6 and 6.0% in USA and UK, respectively. CONCLUSIONS: Taking account of shortcomings in the study base and methodological concerns, we confirm the alcohol-breast cancer association. We compared our results to those of an individual patient data analysis, with similar findings. We conclude that the association between alcohol and breast cancer may be causal.

Studying time to pregnancy by use of a retrospective design.

Biologic fertility can be measured using time to pregnancy (TTP). Retrospective designs, although lacking detailed timed information about behavior and exposure, are useful since they have a well-defined target population, often have good response rates, and are simpler and less expensive to conduct than prospective studies. This paper reviews retrospective TTP studies from a methodological viewpoint and shows how methodological problems can be avoided or minimized by appropriate study design, conduct, and analysis. Sensitivity analyses using data from four European retrospective TTP studies are presented to explore the issues. Although the identified biases tend to have small impacts, the effects are not systematic across studies, and sensitivity analyses are recommended routinely. Planning bias can be checked by comparing propensity to report contraceptive failures in different exposure groups. Medical intervention bias can be avoided by censoring and inclusion of unsuccessful pregnancy attempts. Truncation bias can be a serious problem if unrecognized, but it is avoidable with appropriate study design and/or analysis. Behavior change bias can be minimized by assessing the covariates at the beginning of unprotected intercourse. More complete inference is possible if the study design covers the whole population, not just those who achieve a pregnancy.