Search

BACKGROUND: Performance status (PS) is a good prognostic factor in lung cancer and is used to assess chemotherapy appropriateness. Researchers studying chemotherapy use are often hindered by the unavailability of PS in automated data sources. To the authors' knowledge, no attempts have been made to estimate PS using claims-based measures. The current study explored the ability to estimate PS using routinely available measures. METHODS: A cohort of insured patients aged ≥50 years who were diagnosed with American Joint Committee on Cancer stage II through IV lung cancer between 2000 and 2007 was identified via a tumor registry (n = 552). PS was abstracted from medical records. Automated medical and pharmaceutical claims from the year preceding diagnosis were linked to tumor registry data. A logistic regression model was fit to estimate good versus poor PS in a random half of the sample. C statistics, sensitivity, specificity, and R² were used to compare the predictive ability of models that included demographic factors, comorbidity measures, and claims-based utilization variables. Model fit was evaluated in the other half of the sample. RESULTS: PS was available in 80% of medical records. The multivariable regression model predicted good PS with high sensitivity (0.88 or 0.94 depending on how good PS was defined), but moderate specificity (0.45 or 0.32) with a 0.50 prediction cutoff, and good sensitivity (0.64 or 0.83) and specificity (0.69 or 0.55) when the cutoff was 0.70. The goodness-of-fit c statistic was 0.76 or 0.78. CONCLUSIONS: PS can be estimated, with some accuracy, using claims-based measures. Emphasis should be placed on documenting PS in medical records and tumor registries. [ABSTRACT FROM AUTHOR]

Objective: Patient–oncologist therapeutic alliance is a foundation of quality cancer care, although there is limited research demonstrating its relationship with patient outcomes. We investigated the relationship between therapeutic alliance and patient quality of life with a secondary goal of determining whether the association varied by patients' baseline level of psychological distress. Methods: Cross‐sectional analysis of baseline data from a randomized clinical trial of 672 patients with advanced cancer participating in a primary palliative care intervention trial. Patients completed baseline self‐reported measures of therapeutic alliance (The Human Connection Scale, range: 16–64), overall quality of life (Functional Assessment of Cancer Therapy—Palliative Care, range: 0–184), and psychological distress (Hospital Anxiety and Depression Scale, range: 0–42). First, we determined the relationship between therapeutic alliance and quality of life using multivariable regression adjusting for confounders. We then examined if psychological distress was an effect modifier in this relationship by adding interaction effects of depression and anxiety symptoms on therapeutic alliance into the regression model. Results: Patients reported high levels of therapeutic alliance (56.4 ± 7.4) and moderate quality of life (130.3 ± 25.5). Stronger therapeutic alliance was associated with better quality of life after adjusting for other confounding factors (β = 3.7, 95% confidence interval = 2.1, 5.3, p < 0.01). The relationship between therapeutic alliance and quality of life was generally consistent regardless of psychological distress. Conclusions: Collaborative, trusting relationships between patients with advanced cancer and their oncologists are associated with better patient quality of life. Future research should investigate the causal, longitudinal nature of these relationships. [ABSTRACT FROM AUTHOR]

Applied coping research has generally failed to fulfill its goal of providing an empirical basis for clinical interventions, and research on coping with cancer is no exception. This can be attributed in large measure to the wide gap between coping theory and coping research. Theories of stress and adaptation are complex systems formulations that present conceptual and methodological challenges and thus make testing comprehensive models difficult. The present paper reviews arguments for a microanalytic strategy through which researchers can increase coverage of relevant variables from broad systems models of stress and coping by concentrating their resources on selected, high-frequency, high-stress problems. The utility of this approach for formulating problem-specific systems models is illustrated using the example of coping with somatic distress among cancer survivors. Copyright © 1999 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Objectives: Patients with cancer who are at a transition to Phase I investigational treatments have been identified as an underserved population with regard to palliative care. This disease transition is often accompanied by spiritual and existential concerns. The study objective was to conduct a secondary analysis of data from a larger study testing a palliative care intervention. This paper reports the findings of this secondary focus on the spiritual needs of this population.Methods: Patients (n = 479) were accrued to this study prior to initiating a Phase I clinical trial with data collected at baseline, and 4, 12, and 24 week follow-up.Results: Qualitative data revealed that the transition to Phase 1 trial participation is a time of balancing hope for extended life with the reality of advancing disease. Quantitative results demonstrated increased spirituality over time in both religious- and non-religious-affiliated patients.Conclusions: Patients entering Phase I trials have important spiritual needs as they face treatment decisions, advancing disease, and often mortality. Spiritual care should be provided to seriously ill patients as a component of quality care. [ABSTRACT FROM AUTHOR]