The impact of population heterogeneity on risk estimation in genetic counseling

BACKGROUND: Genetic counseling has been an important tool for evaluating and communicating disease susceptibility for decades, and it has been applied to predict risks for a wide class of hereditary disorders. Most diseases are complex in nature and are affected by multiple genes and environmental conditions; it is highly likely that DNA tests alone do not define all the genetic factors responsible for a disease, so that persons classified into the same risk group by DNA testing actually could have different disease susceptibilities. Ignorance of population heterogeneity may lead to biased risk estimates, whereas additional information on population heterogeneity may improve the precision of such estimates. METHODS: Although DNA tests are widely used, few studies have investigated the accuracy of the predicted risks. We examined the impact of population heterogeneity on predicted disease risks by simulation of three different heterogeneity scenarios and studied the precision and accuracy of the risks estimated from a logistic regression model that ignored population heterogeneity. Moreover, we also incorporated information about population heterogeneity into our original model and investigated the resulting improvement in the accuracy of risk estimation. RESULTS: We found that heterogeneity in one or more categories could lead to biased estimates not only in the "contaminated" categories but also in other homogeneous categories. Incorporating information about population heterogeneity into the original model greatly improved the accuracy of risk estimation. CONCLUSIONS: Our findings imply that without thorough knowledge about genetic basis of the disease, risks estimated from DNA tests may be misleading. Caution should be taken when evaluating the predicted risks obtained from genetic counseling. On the other hand, the improved accuracy of risk estimates after incorporating population heterogeneity information into the model did point out a promising direction for genetic counseling, since more and more new techniques are being invented and disease etiology is being better understood

Dynamic predicting by landmarking as an alternative for multi-state modeling: an application to acute lymphoid leukemia data

This paper considers the problem of obtaining a dynamic prediction for 5-year failure free survival after bone marrow transplantation in ALL patients using data from the EBMT, the European Group for Blood and Marrow Transplantation. The paper compares the new landmark methodology as developed by the first author and the established multi-state modeling as described in a recent Tutorial in Biostatistics in Statistics in Medicine by the second author and colleagues. As expected the two approaches give similar results. The landmark methodology does not need complex modeling and leads to easy prediction rules. On the other hand, it does not give the insight in the biological processes as obtained for the multi-state model

Outcome based subgroup analysis: a neglected concern

A subgroup of clinical trial subjects identified by baseline characteristics is a proper subgroup while a subgroup determined by post randomization events or measures is an improper subgroup. Both types of subgroups are often analyzed in clinical trial papers. Yet, the extensive scrutiny of subgroup analyses has almost exclusively attended to the former. The analysis of improper subgroups thereby not only flourishes in numerous disguised ways but also does so without a corresponding awareness of its pitfalls. Comparisons of the grade of angina in a heart disease trial, for example, usually include only the survivors. This paper highlights some of the distinct ways in which outcome based subgroup analysis occurs, describes the hazards associated with it, and proposes a simple alternative approach to counter its analytic bias. Data from six published trials show that outcome based subgroup analysis, like proper subgroup analysis, may be performed in a post-hoc fashion, overdone, selectively reported, and over interpreted. Six hypothetical trial scenarios illustrate the forms of hidden bias related to it. That bias can, however, be addressed by assigning clinically appropriate scores to the usually excluded subjects and performing an analysis that includes all the randomized subjects. A greater level of awareness about the practice and pitfalls of outcome based subgroup analysis is needed. When required, such an analysis should maintain the integrity of randomization. This issue needs greater practical and methodologic attention than has been accorded to it thus far

Modelling the effects of standard prognostic factors in node-positive breast cancer

Prognostic models that predict the clinical course of a breast cancer patient are important in oncology. We propose an approach to constructing such models based on fractional polynomials in which useful transformations of the continuous factors are determined. The idea may be applied with all types of regression model, including Cox regression, the method of choice for survival-time data. We analyse a prospective study of node-positive breast cancer. Seven standard prognostic factors – age, menopausal status, tumour size, tumour grade, number of positive lymph nodes, progesterone and oestrogen receptor concentrations – were investigated in 686 patients, of whom 299 had an event for recurrence-free survival and 171 died. We determine a final model with transformations of prognostic factors and compare it with the more traditional approaches using categorized variables or assuming a straight line relationship. We conclude that analysis using fractional polynomials can extract important prognostic information which the traditional approaches may miss. © 1999 Cancer Research Campaig

Estimating time-to-onset of adverse drug reactions from spontaneous reporting databases.

International audienceBACKGROUND: Analyzing time-to-onset of adverse drug reactions from treatment exposure contributes to meeting pharmacovigilance objectives, i.e. identification and prevention. Post-marketing data are available from reporting systems. Times-to-onset from such databases are right-truncated because some patients who were exposed to the drug and who will eventually develop the adverse drug reaction may do it after the time of analysis and thus are not included in the data. Acknowledgment of the developments adapted to right-truncated data is not widespread and these methods have never been used in pharmacovigilance. We assess the use of appropriate methods as well as the consequences of not taking right truncation into account (naïve approach) on parametric maximum likelihood estimation of time-to-onset distribution. METHODS: Both approaches, naïve or taking right truncation into account, were compared with a simulation study. We used twelve scenarios for the exponential distribution and twenty-four for the Weibull and log-logistic distributions. These scenarios are defined by a set of parameters: the parameters of the time-to-onset distribution, the probability of this distribution falling within an observable values interval and the sample size. An application to reported lymphoma after anti TNF-¿ treatment from the French pharmacovigilance is presented. RESULTS: The simulation study shows that the bias and the mean squared error might in some instances be unacceptably large when right truncation is not considered while the truncation-based estimator shows always better and often satisfactory performances and the gap may be large. For the real dataset, the estimated expected time-to-onset leads to a minimum difference of 58 weeks between both approaches, which is not negligible. This difference is obtained for the Weibull model, under which the estimated probability of this distribution falling within an observable values interval is not far from 1. CONCLUSIONS: It is necessary to take right truncation into account for estimating time-to-onset of adverse drug reactions from spontaneous reporting databases

Targeting targeted agents: open issues for clinical trial design

Molecularly targeted agents for the treatment of solid tumors had entered the market in the last 5 years, with a great impact upon both the scientific community and the society. Many randomized phase III trials conducted in recent years with new targeted agents, despite previous data coming from preclinical research and from phase II trials were often promising, have produced disappointingly negative results. Some other trials have actually met their primary endpoint, demonstrating a statistically significant result favouring the experimental treatment. Unfortunately, with a few relevant exceptions, this advantage is often small, if not negligible, in absolute terms. The difference between statistical significance and clinical relevance should always be considered when translating clinical trials' results in the practice. The reason why this 'revolution' did not significantly impact on cancer treatment to displace chemotherapy from the patient' bedside is in part due to complicated, and in many cases, unknown, mechanisms of action of such drugs; indeed, the traditional way the clinical investigators were used to test the efficacy of 'older' chemotherapeutics, has become 'out of date' from the methodological perspective. As these drugs should be theoretically tailored upon featured bio-markers expressed by the patients, the clinical trial design should follow new rules based upon stronger hypotheses than those developed so far. Indeed, the early phases of basic and clinical drug development are crucial in the correct process which is able to correctly identify the target (when present). Targeted trial designs can result in easier studies, with less, better selected, and supported by stronger proofs of response evidences, patients, in order to not waste time and resources

Variables with time-varying effects and the Cox model: Some statistical concepts illustrated with a prognostic factor study in breast cancer

International audienceBACKGROUND: The Cox model relies on the proportional hazards (PH) assumption, implying that the factors investigated have a constant impact on the hazard - or risk - over time. We emphasize the importance of this assumption and the misleading conclusions that can be inferred if it is violated; this is particularly essential in the presence of long follow-ups. METHODS: We illustrate our discussion by analyzing prognostic factors of metastases in 979 women treated for breast cancer with surgery. Age, tumour size and grade, lymph node involvement, peritumoral vascular invasion (PVI), status of hormone receptors (HRec), Her2, and Mib1 were considered. RESULTS: Median follow-up was 14 years; 264 women developed metastases. The conventional Cox model suggested that all factors but HRec, Her2, and Mib1 status were strong prognostic factors of metastases. Additional tests indicated that the PH assumption was not satisfied for some variables of the model. Tumour grade had a significant time-varying effect, but although its effect diminished over time, it remained strong. Interestingly, while the conventional Cox model did not show any significant effect of the HRec status, tests provided strong evidence that this variable had a non-constant effect over time. Negative HRec status increased the risk of metastases early but became protective thereafter. This reversal of effect may explain non-significant hazard ratios provided by previous conventional Cox analyses in studies with long follow-ups. CONCLUSIONS: Investigating time-varying effects should be an integral part of Cox survival analyses. Detecting and accounting for time-varying effects provide insights on some specific time patterns, and on valuable biological information that could be missed otherwise

Pre-referral rectal artesunate in severe malaria: flawed trial

<p>Abstract</p> <p>Background</p> <p>Immediate injectable treatment is essential for severe malaria. Otherwise, the afflicted risk lifelong impairment or death. In rural areas of Africa and Asia, appropriate care is often miles away. In 2009, Melba Gomes and her colleagues published the findings of a randomized, placebo-controlled trial of rectal artesunate for suspected severe malaria in such remote areas. Enrolling nearly 18,000 cases, the aim was to evaluate whether, as patients were in transit to a health facility, a pre-referral artesunate suppository blocked disease progression sufficiently to reduce these risks. The affirmative findings of this, the only trial on the issue thus far, have led the WHO to endorse rectal artesunate as a pre-referral treatment for severe malaria. In the light of its public health importance and because its scientific quality has not been assessed for a systematic review, our paper provides a detailed evaluation of the design, conduct, analysis, reporting, and practical features of this trial.</p> <p>Results</p> <p>We performed a checklist-based and an in-depth evaluation of the trial. The evaluation criteria were based on the CONSORT statement for reporting clinical trials, the clinical trial methodology literature, and practice in malaria research. Our main findings are: The inclusion and exclusion criteria and the sample size justification are not stated. Many clearly ineligible subjects were enrolled. The training of the recruiters does not appear to have been satisfactory. There was excessive between center heterogeneity in design and conduct. Outcome evaluation schedule was not defined, and in practice, became too wide. Large gaps in the collection of key data were evident. Primary endpoints were inconsistently utilized and reported; an overall analysis of the outcomes was not done; analyses of time to event data had major flaws; the stated intent-to-treat analysis excluded a third of the randomized subjects; the design-indicated stratified or multi-variate analysis was not done; many improper subgroups were analyzed in a post-hoc fashion; the analysis and reporting metric was deficient. There are concerns relating to patient welfare at some centers. Exclusion of many cases from data analysis compromised external validity. A bias-controlled reanalysis of available data does not lend support to the conclusions drawn by the authors.</p> <p>Conclusions</p> <p>This trial has numerous serious deficiencies in design, implementation, and methods of data analysis. Interpretation and manner of reporting are wanting, and the applicability of the findings is unclear. The trial conduct could have been improved to better protect patient welfare. The totality of these problems make it a flawed study whose conclusions remain subject to appreciable doubt.</p

Monitoring microbicide gel use with real-time notification of the container’s opening events : results of the CAPRISA Wisebag study.

CAPRISA, 2014.Accurate estimation of the effectiveness of a microbicide for HIV prevention requires valid measurement of adherence to product use. A microbicide gel applicator container (Wisebag), fitted with cell phone technology to transmit opening events and text message reminders, was developed to monitor each opening event of the container as a proxy for gel use and adherence. Ten women were enrolled in a pilot study and followed for up to 4 months. Wisebag opening (WBO) dates and times were recorded and correlated with self-reported sex acts and gel applicator returns. During the 33 monthly follow-up visits, 47.8% (77/161) of the recorded number of WBO events were concordant with the number of empty (used) applicators returned. The discrepancies were likely due to removal of more than one applicator during a single opening event. When the date and time of the WBO event data was assessed in relation to three different self-report adherence measures, agreement was fairly modest. The Wisebag was found to be acceptable as a storage container and the cell phone reminders generated were useful in supporting the dosing strategy. We recommend that the Wisebag be considered for larger scale and lengthier testing in microbicide trials

Volunteer Bias in Recruitment, Retention, and Blood Sample Donation in a Randomised Controlled Trial Involving Mothers and Their Children at Six Months and Two Years: A Longitudinal Analysis

BACKGROUND: The vulnerability of clinical trials to volunteer bias is under-reported. Volunteer bias is systematic error due to differences between those who choose to participate in studies and those who do not. METHODS AND RESULTS: This paper extends the applications of the concept of volunteer bias by using data from a trial of probiotic supplementation for childhood atopy in healthy dyads to explore 1) differences between a) trial participants and aggregated data from publicly available databases b) participants and non-participants as the trial progressed 2) impact on trial findings of weighting data according to deprivation (Townsend) fifths in the sample and target populations. 1) a) Recruits (n = 454) were less deprived than the target population, matched for area of residence and delivery dates (n = 6,893) (mean [SD] deprivation scores 0.09[4.21] and 0.79[4.08], t = 3.44, df = 511, p<0.001). b) i) As the trial progressed, representation of the most deprived decreased. These participants and smokers were less likely to be retained at 6 months (n = 430[95%]) (OR 0.29,0.13-0.67 and 0.20,0.09-0.46), and 2 years (n = 380[84%]) (aOR 0.68,0.50-0.93 and 0.55,0.28-1.09), and consent to infant blood sample donation (n = 220[48%]) (aOR 0.72,0.57-0.92 and 0.43,0.22-0.83). ii) Mothers interested in probiotics or research or reporting infants' adverse events or rashes were more likely to attend research clinics and consent to skin-prick testing. Mothers participating to help children were more likely to consent to infant blood sample donation. 2) In one trial outcome, atopic eczema, the intervention had a positive effect only in the over-represented, least deprived group. Here, data weighting attenuated risk reduction from 6.9%(0.9-13.1%) to 4.6%(-1.4-+10.5%), and OR from 0.40(0.18-0.91) to 0.56(0.26-1.21). Other findings were unchanged. CONCLUSIONS: Potential for volunteer bias intensified during the trial, due to non-participation of the most deprived and smokers. However, these were not the only predictors of non-participation. Data weighting quantified volunteer bias and modified one important trial outcome. TRIAL REGISTRATION: This randomised, double blind, parallel group, placebo controlled trial is registered with the International Standard Randomised Controlled Trials Register, Number (ISRCTN) 26287422. Registered title: Probiotics in the prevention of atopy in infants and children