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Summary Ending the silent pandemic of unsafe abortion is an urgent public-health and human-rights imperative. As with other more visible global-health issues, this scourge threatens women throughout the developing world. Every year, about 19–20 million abortions are done by individuals without the requisite skills, or in environments below minimum medical standards, or both. Nearly all unsafe abortions (97%) are in developing countries. An estimated 68 000 women die as a result, and millions more have complications, many permanent. Important causes of death include haemorrhage, infection, and poisoning. Legalisation of abortion on request is a necessary but insufficient step toward improving women's health; in some countries, such as India, where abortion has been legal for decades, access to competent care remains restricted because of other barriers. Access to safe abortion improves women's health, and vice versa, as documented in Romania during the regime of President Nicolae Ceausescu. The availability of modern contraception can reduce but never eliminate the need for abortion. Direct costs of treating abortion complications burden impoverished health care systems, and indirect costs also drain struggling economies. The development of manual vacuum aspiration to empty the uterus, and the use of misoprostol, an oxytocic agent, have improved the care of women. Access to safe, legal abortion is a fundamental right of women, irrespective of where they live. The underlying causes of morbidity and mortality from unsafe abortion today are not blood loss and infection but, rather, apathy and disdain toward women.

Likelihood ratios can refine clinical diagnosis on the basis of signs and symptoms; however, they are underused for patients' care. A likelihood ratio is the percentage of ill people with a given test result divided by the percentage of well individuals with the same result. Ideally, abnormal test results should be much more typical in ill individuals than in those who are well (high likelihood ratio) and normal test results should be most frequent in well people than in sick people (low likelihood ratio). Likelihood ratios near unity have little effect on decision-making; by contrast, high or low ratios can greatly shift the clinician's estimate of the probability of disease. Likelihood ratios can be calculated not only for dichotomous (positive or negative) tests but also for tests with multiple levels of results, such as creatine kinase or ventilation-perfusion scans. When combined with an accurate clinical diagnosis, likelihood ratios from ancillary tests improve diagnostic accuracy in a synergistic manner.

Summary Investigators should properly calculate sample sizes before the start of their randomised trials and adequately describe the details in their published report. In these a-priori calculations, determining the effect size to detect—eg, event rates in treatment and control groups—reflects inherently subjective clinical judgments. Furthermore, these judgments greatly affect sample size calculations. We question the branding of trials as unethical on the basis of an imprecise sample size calculation process. So-called underpowered trials might be acceptable if investigators use methodological rigor to eliminate bias, properly report to avoid misinterpretation, and always publish results to avert publication bias. Some shift of emphasis from a fixation on sample size to a focus on methodological quality would yield more trials with less bias. Unbiased trials with imprecise results trump no results at all. Clinicians and patients deserve guidance now.

Use of control (comparison) groups is a powerful research tool. In case-control studies, controls estimate the frequency of an exposure in the population under study. Controls can be taken from known or unknown study populations. A known group consists of a defined population observed over a period, such as passengers on a cruise ship. When the study group is known, a sample of the population can be used as controls. If no population roster exists, then techniques such as random-digit dialling can be used. Sometimes, however, the study group is unknown, for example, motor-vehicle crash victims brought to an emergency department, who may come from far away. In this situation, hospital controls, neighbourhood controls, and friend, associate, or relative controls can be used. In general, one well-selected control group is better than two or more. When the number of cases is small, the ratio of controls to cases can be raised to improve the ability to find important differences. Although no ideal control group exists, readers need to think carefully about how representative the controls are. Poor choice of controls can lead to both wrong results and possible medical harm.

Summary Proper randomisation means little if investigators cannot include all randomised participants in the primary analysis. Participants might ignore follow-up, leave town, or take aspartame when instructed to take aspirin. Exclusions before randomisation do not bias the treatment comparison, but they can hurt generalisability. Eligibility criteria for a trial should be clear, specific, and applied before randomisation. Readers should assess whether any of the criteria make the trial sample atypical or unrepresentative of the people in which they are interested. In principle, assessment of exclusions after randomisation is simple: none are allowed. For the primary analysis, all participants enrolled should be included and analysed as part of the original group assigned (an intent-to-treat analysis). In reality, however, losses frequently occur. Investigators should, therefore, commit adequate resources to develop and implement procedures to maximise retention of participants. Moreover, researchers should provide clear, explicit information on the progress of all randomised participants through the trial by use of, for instance, a trial profile. Investigators can also do secondary analyses on, for instance, per-protocol or as-treated participants. Such analyses should be described as secondary and non-randomised comparisons. Mishandling of exclusions causes serious methodological difficulties. Unfortunately, some explanations for mishandling exclusions intuitively appeal to readers, disguising the seriousness of the issues. Creative mismanagement of exclusions can undermine trial validity.

Summary Epidemiologists benefit greatly from having case-control study designs in their research armamentarium. Case-control studies can yield important scientific findings with relatively little time, money, and effort compared with other study designs. This seemingly quick road to research results entices many newly trained epidemiologists. Indeed, investigators implement case-control studies more frequently than any other analytical epidemiological study. Unfortunately, case-control designs also tend to be more susceptible to biases than other comparative studies. Although easier to do, they are also easier to do wrong. Five main notions guide investigators who do, or readers who assess, case-control studies. First, investigators must explicitly define the criteria for diagnosis of a case and any eligibility criteria used for selection. Second, controls should come from the same population as the cases, and their selection should be independent of the exposures of interest. Third, investigators should blind the data gatherers to the case or control status of participants or, if impossible, at least blind them to the main hypothesis of the study. Fourth, data gatherers need to be thoroughly trained to elicit exposure in a similar manner from cases and controls; they should use memory aids to facilitate and balance recall between cases and controls. Finally, investigators should address confounding in case-control studies, either in the design stage or with analytical techniques. Devotion of meticulous attention to these points enhances the validity of the results and bolsters the reader's confidence in the findings.

Summary The randomised controlled trial sets the gold standard of clinical research. However, randomisation persists as perhaps the least-understood aspect of a trial. Moreover, anything short of proper randomisation courts selection and confounding biases. Researchers should spurn all systematic, non-random methods of allocation. Trial participants should be assigned to comparison groups based on a random process. Simple (unrestricted) randomisation, analogous to repeated fair coin-tossing, is the most basic of sequence generation approaches. Furthermore, no other approach, irrespective of its complexity and sophistication, surpasses simple randomisation for prevention of bias. Investigators should, therefore, use this method more often than they do, and readers should expect and accept disparities in group sizes. Several other complicated restricted randomisation procedures limit the likelihood of undesirable sample size imbalances in the intervention groups. The most frequently used restricted sequence generation procedure is blocked randomisation. If this method is used, investigators should randomly vary the block sizes and use larger block sizes, particularly in an unblinded trial. Other restricted procedures, such as urn randomisation, combine beneficial attributes of simple and restricted randomisation by preserving most of the unpredictability while achieving some balance. The effectiveness of stratified randomisation depends on use of a restricted randomisation approach to balance the allocation sequences for each stratum. Generation of a proper randomisation sequence takes little time and effort but affords big rewards in scientific accuracy and credibility. Investigators should devote appropriate resources to the generation of properly randomised trials and reporting their methods clearly.

Summary Background The value of antibiotic prophylaxis before insertion of an intrauterine device (IUD) remains uncertain. We undertook a triple-masked, randomised, placebo-controlled trial to find out whether such prophylaxis reduces the rate of IUD removal within 90 days. Methods 11 clinic sites in southern California enrolled women who requested IUD insertion and were at low risk of sexually transmitted infection according to self-reported medical history. We randomly assigned 1985 participants either 500 mg azithromycin or placebo capsules of identical appearance taken about 1 h before insertion of a Copper T 380A IUD. 118 women did not have an IUD inserted. We followed up 1833 of the remaining 1867 (98%) participants for at least 90 days after insertion. Findings The rate of IUD removal for any reason other than partial expulsion was 3·8% (35/918) in the antibiotic group and 3·4% (31/915) in the placebo group (relative risk 1·1 [95% Cl 0·7–1·8]). The two treatment groups sought medical attention with equal frequency (mean 38 visits per 100 women). During the 90 days after IUD insertion, only one woman from each assignment group had salpingitis, as defined by established criteria. Interpretation Prophylaxis with azithromycin did not affect the likelihood that a woman would retain her IUD at 90 days or the frequency of postinsertion medical attention. In appropriately screened women, the risk of upper-genitaltract infection is negligible after IUD insertion, with or without the administration of prophylactic antibiotics.

Investigators in Oxford have made many contributions to the understanding for the potential relations between contraception genital-tract infections and infertility. A cohort study comparing return to fertility among nulliparas after discontinuation of contraception to become pregnant is an example. In this study long-term IUD use by nulliparas was associated with a delay of childbirth compared with time for those stopping oral contraceptives and barrier methods. The investigators recommended that IUDs should be used sparingly in nulliparous women and that use for many years should be avoided. In addition they speculated that pelvic inflammatory disease might have been the culprit although their study could not explore biological mechanisms. However the reported strong associations between IUDs and upper genital tract infections have been found to be unreliable due to selection bias confounding and because there was a broader definition of the outcome than the etiological hypothesis of the study. A review of the evidence conducted by WHO concludes that the benefits of IUDs for nulliparas outweigh the theoretical or proven risks. Nevertheless nulliparous women are still warned against long-term IUD use in view of the inconsistent evidence of the relations.