Background Multinational clinical trials commonly include different language versions of patient-reported outcomes (PRO) instruments without considering the question of their cross-cultural validity. The inclusion of a PRO instrument, the Adult AIDS Clinical Trial Group Symptom Distress Module (SDM), in an multinational clinical trial in HIV-1 antiretroviral-naive patients offered an opportunity to explore the methods to assess cross-cultural validity of PRO instruments in the context of clinical trials.

Purpose To assess the cross-cultural validity of the SDM across seven cultural groups in the setting of a multinational HIV clinical trial.

Methods Twenty-five language versions of the SDM were included in a Phase IIb/III trial comparing maraviroc with efavirenz (each in combination with zidovudine/lamivudine) conducted in 12 countries to assess symptoms perceived by HIV-1-infected antiretroviral-naive patients. Differential item functioning (DIF) detection and the STATIS method were combined in a pragmatic approach to assess the cross-cultural validity of the SDM using pre-antiretroviral treatment data from 759 patients.

Results Statistically significant DIF between cultural groups was observed for four items: fatigue; fevers; anxiety; and headache. However, examination of these items by linguists did not lead to meaningful explanations for the statistical differences. With the STATIS approach, the Bantu and European Germanic groups were the furthest from the Occidental English group.

Limitations The assessment of cross-cultural validity had to be performed on some very small samples and on data aggregated by cultural groups, which suggests the need for a cautious interpretation of the results.

Conclusions Given the heterogeneity of cultures considered, the absence of meaningful explanations for statistically significant differences between cultural groups supports the cross-cultural validity of the SDM versions included in this trial. Thus, this study demonstrated that it is feasible to conduct assessment of cross-cultural validity of PRO instruments using data collected in the setting of multinational clinical trials.

Background It is highly desirable to terminate a clinical trial early if the emerging data suggests that the experimental treatment is ineffective, or substantially less effective than the level the study was designed to detect. Many studies have used a conditional power calculation as the basis for termination for futility. However, in order to compute conditional power one must posit an assumption about the distribution of the future data yet to be observed, such as that the original design assumptions will apply, or that the future data will have the same treatment effect as that estimated from the current ‘trend’ in the data. Each such assumption will yield a different conditional power value.

Purpose The assessment of futility is described in terms of the observed quantities alone, specifically the interim Z-value or the interim confidence limit on the magnitude of the treatment effect, such that specified type I and II error probabilities are achieved. No assumption is required regarding the distribution of the future data yet to be observed.

Methods Lachin [<xref ref-type="bibr" rid="B1">1</xref>] presents a review of futility stopping based on assessment of conditional power and evaluates the statistical properties of a futility stopping rule. These methods are adapted to futility stopping using only the observed data without any assumption about the future data yet to be observed.

Results The statistical properties of the futility monitoring plan depend specifically on the corresponding boundary value for the interim Z-value. These include the probability of interim stopping under the null or under a specific alternative hypothesis, and the resulting type I and II error probabilities. Thus, the stopping rule can be uniquely specified in terms of a boundary for the interim Z-value. Alternately, the stopping rule can be specified in terms of a boundary on the upper confidence limit for the treatment group effect (favoring treatment). Herein it is shown that this approach is equivalent to a boundary on the test Z-value, from which the operating characteristics of the stopping rule can then be calculated.

Limitations While the statistical properties described herein strictly apply to a pre-specified futility boundary, it is also shown that these methods can be applied in an ad-hoc manner. In the event that a sequence of interim assessments for futility is desired, other sequential methods with an outer effectiveness boundary and inner futility boundary would be preferred.

Conclusions These methods allow the design of clinical trials that have specified operating characteristics with a pre-specified futility analysis based only on the interim quantities that have been observed. Examples are presented.

Purpose To assess cancer clinical trial recruitment and reasons for nonaccrual among a rural, medically underserved population served by a community-based cancer care center.

Methods We prospectively tracked clinical trial enrollment incidence among all new patients presenting at the Rapid City Regional Cancer Care Institute. Evaluating physicians completed questionnaires for each patient regarding clinical trial enrollment status and primary reasons for nonenrollment. Patients who identified as American Indian were referred to a program where patients were assisted in navigating the medical system by trained, culturally competent staff.

Results Between September 2006 and January 2008, 891 new cancer patients were evaluated. Seventy-eight patients (9%; 95% confidence intervals, 7–11%) were enrolled on a clinical treatment trial. For 73% (95% confidence intervals, 69–75%) of patients (646 of 891) lack of relevant protocol availability or protocol inclusion criteria restrictiveness was the reason for nonenrollment. Only 45 (5%; 95% confidence intervals, 4–7%) patients refused enrollment on a trial. Of the 78 enrolled on a trial, 6 (8%; 95% confidence intervals, 3–16%) were American Indian. Three additional American Indian patients were enrolled under a nontreatment cancer control trial, bringing the total percentage enrolled of the 94 American Indians who presented to the clinic to 10% (95% confidence intervals, 5–17%).

Limitations Eligibility rates were unable to be calculated and cross validation of the number in the cohort via registries or ICD-9 codes was not performed.

Conclusion Clinical trial participation in this medically underserved population was low overall, but approximately 3-fold higher than reported national accrual rates. Lack of availability of protocols for common cancer sites as well as stringent protocol inclusion criteria were the primary obstacles to clinical trial enrollment. Targeted interventions using a Patient Navigation program were used to engage AI patients and may have resulted in higher clinical trial enrollment among this racial/ethnic group.

Background Recent data indicate that lithium use for bipolar disorder has declined over the last decade and that lithium largely has been replaced with alternate, commercially promoted medications that may or may not result in better outcomes.

Purpose This article describes the rationale and study design of LiTMUS, a multi-site, prospective, randomized clinical trial of outpatients with bipolar disorder. LiTMUS seeks to address whether initiating therapy at lower doses of lithium as part of optimized treatment (OPT, guideline-informed, evidence-based, and personalized pharmacotherapy) improves outcomes and decreases the need for other medication changes across 6 months of therapy.

Methods LiTMUS will randomize 284 adults with bipolar disorder (Type I or II) across 6 study sites. The co-primary outcomes are overall illness severity on clinical global improvement scale for bipolar disorder and a novel measure, necessary clinical adjustments. This metric provides a composite that reflects both clinical response and tolerability. Other relevant outcomes include full symptomatic recovery, quality of life, suicidal behaviors, and moderators of suicidality.

Results As of August 28th, 2009, we have consented 338 patients and randomized 281 for this study.

Limitations The potential limitations of the study include an arbitrary definition of ‘low, but effective’ doses of lithium, lack of a placebo-controlled group, open treatment, and use of a new outcome measure (i.e., necessary clinical adjustments).

Conclusion We expect that this study will inform our understanding of the effectiveness of low to moderate doses of lithium therapy for individuals with bipolar disorder.

Background Changes in regulatory standards that restrict use of identifiable health information can reduce patient recruitment to clinical trials and increase recruitment costs.

Purpose To compare subject accrual rates and costs of three recruitment strategies that comply with new regulatory standards within the context of a clinical trial evaluating the impact of shared decision-making on colorectal cancer screening adherence.

Methods Sequential cohorts of English-speaking, average-risk patients due for colorectal cancer screening were allocated to one of three recruitment strategies: (1) a provider-initiated electronic ‘opt-in’ referral (Click) method; (2) a provider-mediated ‘opt-in’ referral letter (Letter) method; and (3) an investigator-initiated direct contact ‘opt-out’ (Call) method.

Results During distinct 6-month recruitment periods between March 2005 and April 2006, 100 potential subjects were identified using the Click method, 847 by the Letter method, and 758 by the Call method. After excluding ineligible prescreened patients, accrual rates were higher for the Call method (188 of 531 [35.4%]) than either the Click (12 of 72 [16.7%]; p = 0.002) or Letter (17 of 816 [2.1%]; p < 0.001) methods. The average cost per patient enrolled for the Call ($156) method was competitive with the Click ($129) and substantially lower than the Letter ($1967) methods; the Call method was least expensive if combined with automated patient identification ($99). Data extrapolation suggest it would take 2.4 years at an overall cost of $138,518 to recruit a target sample of 900 patients by the Call method, 40.5 years at $62,419 for the Click method and 27.9 years at $1,737,757 for the Letter method.

Limitations The study was nonrandomized and findings may not be generalizable to other research settings.

Conclusion The investigator-initiated direct contact ‘opt-out’ strategy is significantly more cost-effective and feasible than provider-initiated and provider-mediated ‘opt-in’ strategies for patient recruitment to clinical trials.

Background The concept of risk assessment for clinical trials has been discussed before, but no comprehensive structured procedure leading to risk-adapted quality management has been published so far. Such a procedure is of particular interest for noncommercial trials in order to optimally use the sparse resources.

Purpose To provide a structured procedure for risk analysis in clinical trials. To propose strategies for on-site monitoring adapted to the risks identified.

Results The risk analysis refers to the risk of noncompliance with the main objectives of Good Clinical Practice. It takes into account risks of the study intervention compared to the risks a patient would run if treated outside a protocol as well as further potential risks regarding patient safety, patient rights, or the credibility of results. The risk analysis is based on detailed questionnaires, which are used to draw up (a) an on-site monitoring strategy recommendation, (b) a list of trial-specific tasks to be covered by on-site monitoring, and (c) a specification of further quality management measures e.g., central monitoring measures. The resulting risk-adapted monitoring strategies focus on the trial’s critical aspects, and differ in terms of the recommended extent of on-site activities.

Limitations The effectiveness of the proposed risk analysis and risk-adapted monitoring has not yet been confirmed. However, the ADAMON project (prospective cluster-randomised study of trial-specific adapted strategies for on-site monitoring in combination with additional quality management measures) has been started in Germany to investigate whether a trial-specific, risk-adapted, reduced on-site monitoring strategy is as effective as an intensive monitoring strategy with regard to the occurrence of serious or critical audit findings. Twelve clinical trials planning to recruit more than 3200 patients participate in this investigation.

Conclusions Our proposal will provide sponsor-investigators and other noncommercial sponsors with an instrument that may facilitate risk analysis and the implementation of targeted quality management measures.

Background Even though adverse event (AE) collection and official accounting are mandatory for clinical trials, there are limited detailed guidelines specifying how to summarize the event for reporting in a timely and expeditious manner. This article details the AE and serious adverse event (SAE) reporting summary developed for a large multi-center National Institutes of Health (NIH)-sponsored clinical trial.

Purpose To review and analyze the large volume of AE data reported by 10 sites (806 SAEs and 19,034 AEs from August 2000 to May 2007) the automated SAE summary was developed. It was designed to ensure timeliness and clarity in the complex process of AE review and reporting.

Methods The AE and SAE case report forms (CRFs) as well as the automated SAE summary were developed within a database management system developed by the Data Coordinating Center (DCC) which allowed for web-based data entry at the DCC and 10 sites and offered immediate overall and site-specific reports accessible by the DCC, site, and NIH project staff.

Results The automated SAE summary pulled data from multiple CRFs to create a succinct and informative summary and allowed for prompt and easy reporting to the regulatory agencies. The summary was adaptable to the needs of reviewers because of the availability of multiple search options.

Limitations The advantages discussed in the manuscript include using the summary to identify trends quickly and facilitate the timely reporting of SAEs to the study monitoring entities; disadvantages include using ICD-9 Codes; monitoring open text fields for completeness and quality; and the process of completion of multiple CRFs for the same event.

Conclusions The automated SAE summary was versatile in meeting the needs of multiple individuals. It can be reviewed for safety issues by the DCC, any regulatory agencies and local site Institutional Review Boards as well as the Industry sponsor.

Background Nonadherence, inadequate monitoring, and side-effects result in suboptimal outcomes in ulcerative colitis (UC). We hypothesize that telemanagement for UC will improve symptoms, quality of life, adherence, and decrease costs.

Purpose This article describes the challenges encountered in the design of the home telemanagement in patients with UC trial.

Methods In a randomized trial to assess the effectiveness of telemanagement for UC compared to best available care, 100 patients will be enrolled. Subjects in the intervention arm will complete self-testing with telemanagement weekly; best available care subjects will receive scheduled follow up, educational fact sheets, and written action plans. Telemanagement consists of a home-unit, decision support server, and web-based clinician portal. The home-unit includes a scale and laptop. Subjects will respond to questions about symptoms, side-effects, adherence, and knowledge weekly; subjects will receive action plans after self-testing. Outcome variables to be assessed every 4 months include: disease activity, using the Seo index; quality of life, using the Inflammatory Bowel Disease Questionnaire; adherence, using pharmacy refill data and the Morisky Medication Adherence Scale; utilization of healthcare resources, using urgent care visits and hospitalizations.

Results We encountered several challenges during design and implementation of our trial. First, we selected a randomized controlled trial design. We could have selected a quasiexperimental design to decrease the sample size needed and costs. Second, identification of a control group was challenging. Telemanagement patients received self-care plans and an educational curriculum. Since controls would not receive these interventions, we thought our results would be biased in favor of telemanagement. In addition, we wanted to evaluate the mode of delivery of these components of care. Therefore, we included written action plans and educational materials for patients in the control group (‘best available care’). Third, we could not blind subjects to group assignment. In an attempt to decrease bias, staff was masked to group assignment to decrease measurement bias. Fourth, we selected outcome measures that were not invasive to decrease risks to subjects and to enhance recruitment.

Limitations Our results may not be generalizable as our program is a tertiary center. Further, subjects are not blinded to the intervention potentially resulting in bias; we attempt to minimize this bias by having staff masked to treatment group at the time of assessment of outcome measures.

Conclusions To the best of our knowledge, our trial will be the first randomized controlled trial to evaluate telemedicine in subjects with gastrointestinal disease. We describe several issues encountered in design and implementation of our trial that will aid investigators when planning telemedicine trials in inflammatory bowel disease.