176 research outputs found

    What constitutes a "clinical trial"?: A survey of oncology professionals

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    <p>Abstract</p> <p>Background</p> <p>What constitutes a "clinical trial" is inconsistently defined in the medical literature. With an initiative by Cancer Care Ontario (CCO) to report institutional clinical trials activity across the province of Ontario, Canada, we sought to investigate the variability in the interpretation of the term by local oncology professionals.</p> <p>Methods</p> <p>A survey amongst the physicians and nurses at the Juravinski Cancer Centre at Hamilton Health Sciences, Ontario was conducted. The survey included 12 summaries of local clinical research studies, and respondents were asked which they believed represented a clinical trial. Subsequently, they were asked which of the same 12 studies they believed should be labeled as clinical trials when considering separate definitions provided by CCO and by the Ontario Cancer Research Network (OCRN).</p> <p>Results</p> <p>A total of 66 (54%) of 123 surveys were completed; 32/46 (70%) by physicians, 21/59 (36%) by primary care nurses, and 13/18 (72%) by clinical trial nurses. Without a standardized definition, all studies, 12/12, were considered to be clinical trials by at least 50% of respondents. When provided with the CCO definition only 6/12 studies were considered to be clinical trials by the majority of respondents, while with the OCRN definition it was 9/12 studies. Studies evaluating natural health products, non-traditional medical interventions, and non-randomized studies with standard interventions consistently ranked the lowest, regardless of the definition used.</p> <p>Conclusion</p> <p>Oncology professionals appear to have a broadly inclusive baseline definition of what constitutes a clinical trial. Establishing rigor and consistency in the definition of a clinical trial is important for any program, institutional or jurisdictional based comparisons of clinical trials activity, especially when used as a quality indicator of patient care.</p

    Understanding the attitudes of the elderly towards enrolment into cancer clinical trials

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    BACKGROUND: The optimal cancer treatment for an older population is largely unknown because of the low numbers of elderly patients accrued into clinical trials. This project focuses on the attitudes of the elderly about participation in clinical trials to determine if this is one of the barriers to the involvement of this population in clinical trials. METHODS: The first phase of this study was a self-administered questionnaire mailed to 425 elderly persons with cancer, selected from Princess Margaret Hospital oncology clinics. The second phase consisted of individual semi-structured interviews with cancer patients to assess their attitudes towards cancer, its management and enrolment into cancer clinical trials. RESULTS: Ninety-four patients responded to the survey giving a response rate of 22.1%. Three quarters of respondents stated that they would be willing to participate in a clinical trial. The factors that most influenced older patients' willingness to participate in a cancer study were recommendations from a cancer doctor and the chance that the study treatment may help them feel better. Seventeen survey responders participated in interviews. Common themes from these interviews included patient-physician communication, the referral process, and the role of age in cancer care decision-making. CONCLUSION: Most elderly people, who responded to this survey, are willing to consider participation in cancer clinical trials however, elderly patients do not appear to actively seek clinical trials and few were informed of the availability of clinical trials. Physician barriers and availability of appropriate clinical trials may play a bigger role in preventing accrual of elderly cancer patients into trials

    Competing risk and heterogeneity of treatment effect in clinical trials

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    It has been demonstrated that patients enrolled in clinical trials frequently have a large degree of variation in their baseline risk for the outcome of interest. Thus, some have suggested that clinical trial results should routinely be stratified by outcome risk using risk models, since the summary results may otherwise be misleading. However, variation in competing risk is another dimension of risk heterogeneity that may also underlie treatment effect heterogeneity. Understanding the effects of competing risk heterogeneity may be especially important for pragmatic comparative effectiveness trials, which seek to include traditionally excluded patients, such as the elderly or complex patients with multiple comorbidities. Indeed, the observed effect of an intervention is dependent on the ratio of outcome risk to competing risk, and these risks – which may or may not be correlated – may vary considerably in patients enrolled in a trial. Further, the effects of competing risk on treatment effect heterogeneity can be amplified by even a small degree of treatment related harm. Stratification of trial results along both the competing and the outcome risk dimensions may be necessary if pragmatic comparative effectiveness trials are to provide the clinically useful information their advocates intend

    Determinants of access to experimental antiretroviral drugs in an Italian cohort of patients with HIV: a multilevel analysis

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    <p>Abstract</p> <p>Background</p> <p>Identification of the determinants of access to investigational drugs is important to promote equity and scientific validity in clinical research. We aimed to analyze factors associated with the use of experimental antiretrovirals in Italy.</p> <p>Methods</p> <p>We studied participants in the Italian Cohort of Antiretroviral-Naive Patients (ICoNA). All patients 18 years or older who had started cART (≥ 3 drugs including at least two NRTI) after their enrolment and during 1997-2007 were included in this analysis. We performed a random effect logistic regression analysis to take into account clustering observations within clinical units. The outcome variable was the use of an experimental antiretroviral, defined as an antiretroviral started before commercial availability, in any episode of therapy initiation/change. Use of an experimental antiretroviral obtained through a clinical trial or an expanded access program (EAP) was also analyzed separately.</p> <p>Results</p> <p>A total of 9,441 episodes of therapy initiation/change were analyzed in 3,752 patients. 392 episodes (360 patients) involved an experimental antiretroviral. In multivariable analysis, factors associated with the overall use of experimental antiretrovirals were: number of experienced drugs (≥ 8 drugs versus "naive": adjusted odds ratio [AOR] = 3.71) or failed antiretrovirals(3-4 drugs and ≥ 5 drugs versus 0-2 drugs: AOR = 1.42 and 2.38 respectively); calendar year (AOR = 0.80 per year) and plasma HIV-RNA copies/ml at therapy change (≥ 4 log versus < 2 log: AOR = 1.55). The probability of taking an experimental antiretroviral through a trial was significantly lower for patients suffering from liver co-morbidity(AOR = 0.65) and for those who experienced 3-4 drugs (vs naive) (AOR = 0.55), while it increased for multi-treated patients(AOR = 2.60). The probability to start an experimental antiretroviral trough an EAP progressively increased with the increasing number of experienced and of failed drugs and also increased for patients with liver co-morbidity (AOR = 1.44; p = 0.053). and for male homosexuals (vs heterosexuals: AOR = 1.67). Variability of the random effect associated to clinical units was statistically significant (p < 0.001) although no association was found with specific characteristics of clinical unit examined.</p> <p>Conclusions</p> <p>Among patients with HIV infection in Italy, access to experimental antiretrovirals seems to be influenced mainly by exhaustion of treatment options and not by socio-demographic factors.</p

    Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

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    SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation

    Palliative chemotherapy beyond three courses conveys no survival or consistent quality-of-life benefits in advanced non-small-cell lung cancer

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    This randomised multicentre trial was conducted to establish the optimal duration of palliative chemotherapy in advanced non-small-cell lung cancer (NSCLC). We compared a policy of three vs six courses of new-generation platinum-based combination chemotherapy with regard to effects on quality of life (QoL) and survival. Patients with stage IIIB or IV NSCLC and WHO performance status (PS) 0–2 were randomised to receive three (C3) or six (C6) courses of carboplatin (area under the curve (AUC) 4, Chatelut's formula, equivalent to Calvert's AUC 5) on day 1 and vinorelbine 25 mg m−2 on days 1 and 8 of a 3-week cycle. Key end points were QoL at 18 weeks, measured with EORTC Quality of Life Questionnaire (QLQ)-C30 and QLQ-LC13, and overall survival. Secondary end points were progression-free survival and need of palliative radiotherapy. Two hundred and ninety-seven patients were randomised (C3 150, C6 147). Their median age was 65 years, 30% had PS 2 and 76% stage IV disease. Seventy-eight and 54% of C3 and C6 patients, respectively, completed all scheduled chemotherapy courses. Compliance with QoL questionnaires was 88%. There were no significant group differences in global QoL, pain or fatigue up to 26 weeks. The dyspnoea palliation rate was lower in the C3 arm at 18 and 26 weeks (P<0.05), but this finding was inconsistent across different methods of analysis. Median survival in the C3 group was 28 vs 32 weeks in the C6 group (P=0.75, HR 1.04, 95% CI 0.82–1.31). One- and 2-year survival rates were 25 and 9% vs 25 and 5% in the C3 and C6 arm, respectively. Median progression-free survival was 16 and 21 weeks in the C3 and C6 groups, respectively (P=0.21, HR 0.86, 95% CI 0.68–1.08). In conclusion, palliative chemotherapy with carboplatin and vinorelbine beyond three courses conveys no survival or consistent QoL benefits in advanced NSCLC

    Lymphoma incidence, survival and prevalence 2004–2014 : sub-type analyses from the UK’s Haematological Malignancy Research Network

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    Background: Population-based information about cancer occurrence and survival are required to inform clinical practice and research; but for most lymphomas data are lacking. Methods: Set within a socio-demographically representative UK population of nearly 4 million, lymphoma data (N ¼ 5796) are from an established patient cohort. Results: Incidence, survival (overall and relative) and prevalence estimates for 420 subtypes are presented. With few exceptions, males tended to be diagnosed at younger ages and have significantly (Po0.05) higher incidence rates. Differences were greatest at younger ages: the o15 year male/female rate ratio for all subtypes combined being 2.2 (95% CI 1.3–3.4). These gender differences impacted on prevalence; most subtype estimates being significantly (Po0.05) higher in males than females. Outcome varied widely by subtype; survival of patients with nodular lymphocyte predominant Hodgkin lymphoma approached that of the general population, whereas less than a third of those with other B-cell (e.g., mantle cell) or T-cell (e.g., peripheral-T) lymphomas survived for Z5 years. No males/female survival differences were detected. Conclusions: Major strengths of our study include completeness of ascertainment, world-class diagnostics and generalisability. The marked variations demonstrated confirm the requirement for ‘real-world’ data to inform aetiological hypotheses, health-care planning and the future monitoring of therapeutic changes

    Towards Universal Structure-Based Prediction of Class II MHC Epitopes for Diverse Allotypes

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    The binding of peptide fragments of antigens to class II MHC proteins is a crucial step in initiating a helper T cell immune response. The discovery of these peptide epitopes is important for understanding the normal immune response and its misregulation in autoimmunity and allergies and also for vaccine design. In spite of their biomedical importance, the high diversity of class II MHC proteins combined with the large number of possible peptide sequences make comprehensive experimental determination of epitopes for all MHC allotypes infeasible. Computational methods can address this need by predicting epitopes for a particular MHC allotype. We present a structure-based method for predicting class II epitopes that combines molecular mechanics docking of a fully flexible peptide into the MHC binding cleft followed by binding affinity prediction using a machine learning classifier trained on interaction energy components calculated from the docking solution. Although the primary advantage of structure-based prediction methods over the commonly employed sequence-based methods is their applicability to essentially any MHC allotype, this has not yet been convincingly demonstrated. In order to test the transferability of the prediction method to different MHC proteins, we trained the scoring method on binding data for DRB1*0101 and used it to make predictions for multiple MHC allotypes with distinct peptide binding specificities including representatives from the other human class II MHC loci, HLA-DP and HLA-DQ, as well as for two murine allotypes. The results showed that the prediction method was able to achieve significant discrimination between epitope and non-epitope peptides for all MHC allotypes examined, based on AUC values in the range 0.632–0.821. We also discuss how accounting for peptide binding in multiple registers to class II MHC largely explains the systematically worse performance of prediction methods for class II MHC compared with those for class I MHC based on quantitative prediction performance estimates for peptide binding to class II MHC in a fixed register
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