A comprehensive review of predictive and prognostic composite factors implicated in the heterogeneity of treatment response and outcome across disease areas.

AIM: To assess and present the current body of evidence regarding composite measures associated with differential treatment response or outcome as a result of patient heterogeneity and to evaluate their consistency across disease areas. METHODS: A comprehensive review of the literature from the last 10 years was performed using three databases (PubMed, Embase and Cochrane). All articles that met the inclusion/exclusion criteria were selected, abstracted and assessed using the NICE level-of-evidence criteria. RESULTS: Forty-nine studies were identified in the data abstraction. Approximately one-third focused on existing composite measures, and the rest investigated emerging composite factors. The majority of studies targeted patients with cancer, cardiovascular disease or psychological disorders. As a whole, the composite measures were found to be disease-specific, but some composite elements, including age, gender, comorbidities and health status, showed consistency across disease areas. To complement these findings, common individual factors found in five previous independent disease-specific literature assessments were also summarised, including age, gender, treatment adherence and satisfaction, healthcare resource utilisation and health status. CONCLUSIONS: Composite measures can play an important role in characterising heterogeneity of treatment response and outcome in patients suffering from various medical conditions. These measures can help clinicians to better distinguish between patients with high likelihood to respond well to treatment and patients with minimal chances of positive therapeutic outcomes. Herein, the individual factors identified can be used to develop novel predictive or prognostic composite measures that can be applicable across disease areas. Reflecting these cross-disease measures in clinical and public health decisions has the distinctive appeal to enable targeted treatment for patients suffering from multiple medical conditions, which may ultimately yield significant gains in individual outcomes, population health and cost-effective resource allocation.

A review of treatment response in type 2 diabetes: assessing the role of patient heterogeneity.

The response to treatment for type 2 diabetes typically varies among individuals within a study population. This variation is known as heterogeneity of treatment response. We conducted a comprehensive literature review to identify factors that account for heterogeneity of treatment response in patients treated for type 2 diabetes. Three databases (PubMed, EMBASE and Cochrane Library) were searched for articles published in the last 10 years describing investigations of factors associated with treatment response and outcomes among people with type 2 diabetes receiving pharmacological treatment. Of the 43 articles extracted and summarized, 35 (81%) discussed clinical factors, 31 (72%) described sociodemographic factors and 17 (40%) reported on comorbidity or behavioural factors. Clinical factors identified included baseline glycated hemoglobin A1c or fasting plasma glucose (FPG) levels, insulin response or sensitivity, C-peptide, body composition, adipose tissue proteins, lipid profile, plasma albumin levels and duration of disease or insulin treatment. Other factors identified included age, sex, race, socioeconomic status and comorbidities. This review identified the following research gaps: use of multiple definitions for response, few patient-reported measures and lack of evidence regarding whether factors were associated with treatment response for only specific medications or across pharmacological therapies. Furthermore, identification of factors associated with type 2 diabetes treatment response was generally a secondary objective in the research reviewed. Understanding which patient subgroups are more likely to respond to treatment and identifying factors associated with response may result in targeted treatment decisions and alter the interpretation of efficacy or effectiveness of results. In conclusion, accounting for these factors in clinical trials and when making clinical treatment decisions may improve therapy selection and individual patient outcomes.

Early lessons from the integration of tuberculosis and HIV services in primary care centers in Lusaka, Zambia.

BACKGROUND: Zambia faces overlapping tuberculosis (TB) and human immunodeficiency virus (HIV) epidemics; however, care for co-infected patients often occurs through separate, vertical programs. OBJECTIVE: To establish a program to integrate TB and HIV services in Lusaka primary care centers. METHODS: In collaboration with the Zambian Ministry of Health, TB-HIV integration activities began in December 2005 and were expanded to seven health centers by March 2007. Principal activities included developing staff capacity to manage co-infected patients, implementing HIV testing within TB departments and establishing referral systems between departments. RESULTS: Using a provider-initiated approach, 2053 TB patients were offered HIV testing. Seventy-seven per cent agreed to be tested; 69% of those tested were HIV-infected. Of these, 59% were enrolled in HIV care. The proportion of antiretroviral treatment (ART) program enrollees who were TB-HIV co-infected increased by 38% after program implementation. The median CD4 count among co-infected patients was 161 cells/microl, with 88% eligible for ART. CONCLUSION: Integration of HIV testing and referral services into urban primary care centers identified many co-infected patients and significantly increased the proportion of TB patients among people accessing HIV care. Ongoing challenges include maximizing the number of patients accepting HIV testing and overcoming barriers to enrollment into HIV care.

Community-based follow-up for late patients enrolled in a district-wide programme for antiretroviral therapy in Lusaka, Zambia.

Timely adherence to clinical and pharmacy appointments is well correlated with favourable patient outcomes among HIV-infected individuals on antiretroviral therapy. To date, however, there is little work exploring reasons behind missed visits or evaluating programmatic strategies to recall patients. For this study we implemented community-based follow-up of late patients as part of a large-scale programme for HIV care and treatment in Lusaka, Zambia. Through a network of local home-based care organizations, we attempted home visits to recall patients using locator information provided at time of enrolment. Between May and September 2005, home-based caregivers were dispatched to trace 1,343 patients with missed appointments. Of these, 554 (41%) were untraceable because the provided address was invalid, the patient had moved or no one was at the home. Of the remaining 789, 359 (46%) were reported to have died. Only 430 (54% of those traced, 32% overall) were contacted directly and encouraged to return for care. The likelihood of patient return was higher among traced patients in crude analysis (relative risk [RR] = 2.5; 95%CI = 1.9-3.2) and in multivariable analysis controlling for baseline body mass index, sex and CD4 + count < or = 50/microL (adjusted RR = 2.3; 95%CI = 1.7-3.2). However, the process was inefficient: one late patient returned for every 18 home visits that were made. Reasons for missed visits were provided in 271 of 430 (63%) of the patients who were successfully traced. Common reasons included feeling too sick to come to the clinic, travelling away from home and being too busy. Despite the availability of free ART in Lusaka, patients face significant barriers to attending scheduled clinical visits. Cost-effective and feasible strategies are urgently needed to improve timely patient follow-up.