Participation of older newly-diagnosed cancer patients in an observational prospective pilot study: an example of recruitment and retention

<p>Abstract</p> <p>Background</p> <p>There have been few prospective observational studies which recruited older newly-diagnosed cancer patients, and of these only some have reported information on the number needed to screen to recruit their study sample, and the number and reasons for refusal and drop-out. This paper reports on strategies to recruit older newly-diagnosed cancer patients prior to treatment into an observational prospective pilot study and to retain them during a six-month period.</p> <p>Methods</p> <p>Medical charts of all patients in the Segal Cancer Centre aged 65 and over were screened and evaluated for inclusion. Several strategies to facilitate recruitment and retention were implemented. Reasons for exclusion, refusal and loss to follow-up were recorded. Descriptive statistics were used to report the reasons for refusal and loss to follow-up. A non-response analysis using chi-square tests and t-tests was conducted to compare respondents to those who refused to participate and to compare those who completed the study to those who were lost to follow-up. A feedback form with open-ended questions was administered following the last interview to obtain patient's opinions on the length of the interviews and conduct of this pilot study.</p> <p>Results</p> <p>3060 medical charts were screened and 156 eligible patients were identified. Of these 112 patients participated for a response rate of 72%. Reasons for refusal were: feeling too anxious (40%), not interested (25%), no time (12.5%), too sick (5%) or too healthy (5%) or other reasons (5%). Ninety-one patients participated in the six-month follow-up (retention 81.3%), seven patients refused follow-up (6.2%) and fourteen patients died (12.5%) during the course of the study. The median time to conduct the baseline interview was 45 minutes and 57% of baseline interviews were conducted at home. Most patients enjoyed participation and only five felt that the interviews were too long.</p> <p>Conclusion</p> <p>It was feasible to recruit newly-diagnosed cancer patients prior to treatment although it required considerable time and effort. Once patients were included, the retention rate was high despite the fact that most were undergoing active cancer treatment.</p

Limited-Stage Small Cell Lung Cancer: Current Chemoradiotherapy Treatment Paradigms

The article reviews the currently available treatment options for patients with limited-stage small cell lung cancer

Phenotypic and molecular characteristics associated with various domains of quality of life in oncology patients and their family caregivers

PURPOSE: Not all oncology patients and their family caregivers (FCs) experience the same quality of life (QOL). The purposes of this study were to identify latent classes of oncology patients (n=168) and their FCs (n=85) with distinct physical, psychological, social, and spiritual well-being trajectories from prior to through four months after the completion of radiation therapy and to evaluate for demographic, clinical, and genetic characteristics that distinguished between these latent classes. METHODS: Using growth mixture modelling, two latent classes were found for three (i.e., physical, psychological, and social well-being) of the four QOL domains evaluated. RESULTS: Across these three domains, the largest percentage of participants reported relatively high well-being scores across the six months of the study. Across these three QOL domains, patients and FCs who were younger, female, belonged to an ethnic minority group, had children at home, had multiple comorbid conditions, or had a lower functional status were more likely to be classified in the lower QOL class. The social well-being domain was the only domain that had a polymorphism in nuclear factor kappa beta 2 (NFKB2) associated with latent class membership. Carrying one or two doses of the rare allele for rs7897947 was associated with a 52% decrease in the odds of belonging to the lower social well-being class (OR (95% CI) = .46 (.21, .99), p=.049). CONCLUSIONS: These findings suggest that a number of phenotypic and molecular characteristics contribute to differences in QOL in oncology patients and their FCs