Analysis of cause of death: Competing risks or progressive illness-death model?

The analysis of cause of death is increasingly becoming a topic in oncology. It is usually distinguished between disease-related and disease-unrelated death. A frequently used approach is to define death as disease-related when a progression to advanced phases has occurred before, otherwise as disease-unrelated. The data are often analyzed as competing risks, while a progressive illness-death model might in fact describe the situation more precisely. In this study, we investigated under which circumstances this misspecification leads to biased estimations of the state occupation probabilities. We simulated data according to the progressive illness-death model in various settings, analyzed them with a competing risks model and with a progressive illness-death model and compared them to the true state occupation probabilities. Censoring was either added independently of the status or based on the patients' status. The simulations showed that the censoring mechanism was decisive for the bias while neither the progression hazard nor the Markov property was important. Further, we found a slightly increased standard deviation for the competing risk estimator when censoring was independent of the patients' status. For illustration, both methods were applied to two practical examples of chronic myeloid leukemia (CML): one randomized controlled trial and one registry data set. While in the first case both estimators yielded almost identical results, in the latter case, visible differences were found between both methods.

[The behavioral and psychological symptoms of dementia in down syndrome (BPSD-DS) scale: comprehensive assessment of psychopathology in down syndrome]. / De BPSD-DS evaluatieschaal voor dementiegerelateerde gedragsveranderingen bij mensen met downsyndroom.

Behavioral and psychological symptoms of dementia (BPSD) have not been comprehensively studied in people with Down syndrome, despite their high risk on dementia. A novel evaluation scale was developed to identify the nature, frequency and severity of behavioral changes (83 behavioral items in 12 clinically defined sections). Central aim was to identify items that change in relation to the dementia status. Structured interviews were conducted with informants of people with Down syndrome without dementia (DS, N = 149), with questionable dementia (DS + TD, N = 65) and with diagnosed dementia (DS + AD, N = 67). Group comparisons showed a pronounced increase in frequency and severity of items about anxiety, sleep disturbances, agitation & stereotypical behavior, aggression, apathy, depressive symptoms, and, eating/drinking behavior. The proportion of individuals presenting an increase was highest in the DS + AD group and lowest in the DS group. Interestingly, among DS + TD individuals, a substantial proportion already presented increased anxiety, sleep disturbances, apathy and depressive symptoms, suggesting that these changes may be early alarm signals of dementia. The scale may contribute to a better understanding of the changes, adapting daily care/support, and providing suitable therapies to people with Down syndrome. The scale needs to be optimized based on the results and experiences. The applicability, reliability and validity require further study.

Course and predictors of supportive care needs among Mexican breast cancer patients: A longitudinal study.

OBJECTIVE: This study examined the course and predictors of supportive care needs among Mexican breast cancer patients for different cancer treatment trajectories. METHODS: Data from 172 (66.4% response rate) patients were considered in this observational longitudinal study. Participants were measured after diagnosis, neoadjuvant treatment, surgery, adjuvant treatment, and the first post-treatment follow-up visit. Psychological, Health System and Information, Physical and Daily Living, Patient Care and Support, Sexual, and Additional care needs were measured with the Supportive Care Needs Survey (SCNS-SF34). Linear mixed models with maximum-likelihood estimation were computed. RESULTS: The course of supportive care needs was similar across the different cancer treatment trajectories. Supportive care needs declined significantly from diagnosis to the first post-treatment follow-up visit. Health System and Information care needs were the highest needs over time. Depressive symptoms and time since diagnosis were the most consistent predictors of changes in course of supportive care needs of these patients. CONCLUSIONS: Health system and information care needs of Mexican breast cancer patients need to be addressed with priority because these needs are the least met. Furthermore, patients with high depressive symptoms at the start of the disease trajectory have greater needs for supportive care throughout the disease trajectory.

The Behavioral and Psychological Symptoms of Dementia in Down Syndrome (BPSD-DS) Scale: Comprehensive Assessment of Psychopathology in Down Syndrome.

People with Down syndrome (DS) are prone to develop Alzheimer's disease (AD). Behavioral and psychological symptoms of dementia (BPSD) are core features, but have not been comprehensively evaluated in DS. In a European multidisciplinary study, the novel Behavioral and Psychological Symptoms of Dementia in Down Syndrome (BPSD-DS) scale was developed to identify frequency and severity of behavioral changes taking account of life-long characteristic behavior. 83 behavioral items in 12 clinically defined sections were evaluated. The central aim was to identify items that change in relation to the dementia status, and thus may differentiate between diagnostic groups. Structured interviews were conducted with informants of persons with DS without dementia (DS, n = 149), with questionable dementia (DS+Q, n = 65), and with diagnosed dementia (DS+AD, n = 67). First exploratory data suggest promising interrater, test-retest, and internal consistency reliability measures. Concerning item relevance, group comparisons revealed pronounced increases in frequency and severity in items of anxiety, sleep disturbances, agitation & stereotypical behavior, aggression, apathy, depressive symptoms, and eating/drinking behavior. The proportion of individuals presenting an increase was highest in DS+AD, intermediate in DS+Q, and lowest in DS. Interestingly, among DS+Q individuals, a substantial proportion already presented increased anxiety, sleep disturbances, apathy, and depressive symptoms, suggesting that these changes occur early in the course of AD. Future efforts should optimize the scale based on current results and clinical experiences, and further study applicability, reliability, and validity. Future application of the scale in daily care may aid caregivers to understand changes, and contribute to timely interventions and adaptation of caregiving.

A weighted combined effect measure for the analysis of a composite time-to-first-event endpoint with components of different clinical relevance.

Composite endpoints combine several events within a single variable, which increases the number of expected events and is thereby meant to increase the power. However, the interpretation of results can be difficult as the observed effect for the composite does not necessarily reflect the effects for the components, which may be of different magnitude or even point in adverse directions. Moreover, in clinical applications, the event types are often of different clinical relevance, which also complicates the interpretation of the composite effect. The common effect measure for composite endpoints is the all-cause hazard ratio, which gives equal weight to all events irrespective of their type and clinical relevance. Thereby, the all-cause hazard within each group is given by the sum of the cause-specific hazards corresponding to the individual components. A natural extension of the standard all-cause hazard ratio can be defined by a "weighted all-cause hazard ratio" where the individual hazards for each component are multiplied with predefined relevance weighting factors. For the special case of equal weights across the components, the weighted all-cause hazard ratio then corresponds to the standard all-cause hazard ratio. To identify the cause-specific hazard of the individual components, any parametric survival model might be applied. The new weighted effect measure can be tested for deviations from the null hypothesis by means of a permutation test. In this work, we systematically compare the new weighted approach to the standard all-cause hazard ratio by theoretical considerations, Monte-Carlo simulations, and by means of a real clinical trial example.

Acute versus Chronic Myocardial Infarction: Diagnostic Accuracy of Quantitative Native T1 and T2 Mapping versus Assessment of Edema on Standard T2-weighted Cardiovascular MR Images for Differentiation.

Purpose To analyze the diagnostic accuracy of native T1 and T2 mapping compared with visual and quantitative assessment of edema on T2-weighted cardiac magnetic resonance (MR) images to differentiate between acute and chronic myocardial infarction. Materials and Methods This study had institutional ethics committee approval. Written informed consent was obtained from 67 consecutive patients (57 years ± 12; 78% men) with a first acute myocardial infarction, who were prospectively enrolled between April 2011 and June 2015. Four serial 1.5-T MR imaging examinations were performed at 8 days ± 5, 7 weeks ± 2, 3 months ± 0.5, and 6 months ± 1.4 after infarction and included T2-weighted, native T1/T2 mapping, and late gadolinium enhancement MR imaging. Complete follow-up data were obtained in 42 patients. Regional native T1/T2 relaxation time, T2-weighted ratio, and extracellular volume were serially measured in infarcted and remote myocardium. Receiver operating characteristic (ROC) analysis was used to determine the diagnostic accuracy of the MR imaging parameters for discriminating between acute and chronic myocardial infarction. Results Native T1 of infarcted myocardium decreased from 1286 msec ± 99 at baseline to 1077 msec ± 50 at 6 months (P < .0001), whereas T2 decreased from 84 msec ± 10 to 58 msec ± 4 (P < .0001). The T2-weighted ratio decreased from 4.1 ± 1.0 to 2.4 ± 0.6 (P < .0001). Of all the MR imaging parameters obtained, native T1 and T2 yielded the best areas under the ROC curve (AUCs) of 0.975 and 0.979, respectively, for differentiating between acute and chronic myocardial infarction. Visual analysis of the presence of edema at standard T2-weighted cardiac MR imaging resulted in an inferior AUC of 0.863 (P < .01). Conclusion Native T1 and T2 of infarcted myocardium are excellent discriminators between acute and chronic myocardial infarction and are superior to all other MR imaging parameters. Online supplemental material is available for this article.

A systematic model specification procedure for an illness-death model without recovery.

Multi-state models are a flexible tool for analyzing complex time-to-event problems with multiple endpoints. Compared to the Cox regression model with a single endpoint or a summarizing composite endpoint, they can provide a more detailed insight into the disease process. Furthermore, prognosis can be improved by including information from intermediate events occurring during the course of the disease. Different model variants, options and additional assumptions provide many possibilities, but at the same time complicate the implementation of multi-state techniques. So far, no guiding literature is available to specify a multi-state model systematically. The objective of this work was to set up a general specification procedure for an illness-death model that optimizes the model fit and predictive accuracy by stepwise reduction of the model. As an application example, we reanalyzed data from an observational study of 434 ovarian cancer patients with progression as intermediate and death as absorbing state. The technique is described in general terms and can be applied to other illness-death models without recovery. The clock-reset approach was used, implicating that the time was reset to zero after progression. The non-homogeneous semi-Markov characteristic stated that the present time as well as the time between surgery and progression influenced survival after progression. Covariate effects on transitions were estimated and proportionality of transition baseline hazards was tested. The finally developed model optimized the accuracy of predictions for two simulated patients. This stepwise procedure yields parsimonious but targeted multi-state models with well interpretable coefficients and optimized predictive ability, even for smaller data sets.