Saturation is a core guiding principle to determine sample sizes in qualitative research, yet little methodological research exists on parameters that influence saturation. Our study compared two approaches to assessing saturation: code saturation and meaning saturation. We examined sample sizes needed to reach saturation in each approach, what saturation meant, and how to assess saturation. Examining 25 in-depth interviews, we found that code saturation was reached at nine interviews, whereby the range of thematic issues was identified. However, 16 to 24 interviews were needed to reach meaning saturation where we developed a richly textured understanding of issues. Thus, code saturation may indicate when researchers have “heard it all,” but meaning saturation is needed to “understand it all.” We used our results to develop parameters that influence saturation, which may be used to estimate sample sizes for qualitative research proposals or to document in publications the grounds on which saturation was achieved.

Durable control of human immunodeficiency virus (HIV) replication and lack of disease progression in the absence of antiretroviral therapy were studi

Poor adherence to combined antiretroviral therapy (cART) has been shown to be a major determinant of virologic failure, emergence of drug resistant virus, disease progression, hospitalizations, mortality, and health care costs. While high adherence levels can be achieved in both resource-rich and resource-limited settings following initiation of cART, long-term adherence remains a challenge regardless of available resources. Barriers to optimal adherence may originate from individual (biological, socio-cultural, behavioral), pharmacological, and societal factors. Although patients and providers should continuously strive for maximum adherence to cART, there is accumulating evidence that each class of antiretroviral therapy has specific adherence-drug resistance relationship characteristics allowing certain regimens more flexibility than others. There is not a universally accepted measure for cART adherence, since each method has distinct advantages and disadvantages including cost, complexity, accuracy, precision, intrusiveness and bias. Development of a real-time cART adherence monitoring tool will enable the development of novel, pre-emptive adherence-improving strategies. The application of these strategies may ultimately prove to be the most cost-effective method to reduce morbidity and mortality for the individual and decrease the likelihood of HIV transmission and emergence of resistance in the community.

Objective: To describe trends in incidence rates of AIDS-defining cancers (ADCs) and non-AIDS-defining cancers (NADCs) during the HIV epidemic and to evaluate predictors, including the impact of antiretroviral therapy, of cancer development. Design: Retrospective analysis of a multicenter, prospective natural history study including 4498 HIV-infected US military beneficiaries with 33 486 person-years of follow-up. Methods: Predictors evaluated included demographics, clinical data, time-updated CD4 cell counts, HIV viral loads, and antiretroviral history. Time periods were classified as early pre (1984–1990), late pre (1991–1995), early post (1996–2000), and late post (2001–2006) HAART eras. Cox proportional hazard models were used to evaluate the association of specific factors with cancer. Results: Ten percent of HIV-infected persons developed cancer. ADC rates increased between the early and late pre-HAART eras (7.6 and 14.2 cases per 1000 person-years) and have since declined from 5.4 to 2.7 in the early and late HAART eras, respectively (P < 0.001). Rates of NADCs have risen over the four periods (2.9, 2.8, 4.2, 6.7, P = 0.0004). During the late HAART era, 71% of cancers were NADCs. Predictors for ADCs included low CD4 cell count, noncancer AIDS diagnosis, and lack of HAART. NADCs were predicted by increasing age and white race (due to skin cancers). Conclusion: Although the rate of ADCs continues to fall, the rate of NADCs is rising and now accounts for the majority of cancers in HIV-infected persons. The development of NADCs is associated with increasing age among HIV patients. HAART use is protective for ADCs, but did not significantly impact NADCs.

The prevalence and factors associated with overweight/obesity among human immunodeficiency virus (HIV)-infected persons are unknown. We evaluated prospective data from a U.S. Military HIV Natural History Study (1985–2004) consisting of early diagnosed patients. Statistics included multivariate linear regression and longitudinal linear mixed effects models. Of 1682 patients, 2% were underweight, 37% were overweight, and 9% were obese at HIV diagnosis. Multivariate predictors of a higher body mass index (BMI) at diagnosis included more recent year of HIV diagnosis, older age, African American race, and earlier HIV stage (all p<0.05). The majority of patients (62%) gained weight during HIV infection. Multivariate factors associated with a greater increase in BMI during HIV infection included more recent year of diagnosis, lower BMI at diagnosis, higher CD4 count, lower HIV RNA level, lack of AIDS diagnosis, and longer HIV duration (all p<0.05). Nucleoside agents were associated with less weight gain; other drug classes had no significant impact on weight change in the HAART era. HIV-infected patients are increasingly overweight/obese at diagnosis and during HIV infection. Weight gain appears to reflect improved health status and mirror trends in the general population. Weight management programs may be important components of HIV care.