Cardiovascular Diseases And Psychiatric Disorders During The Diagnostic Workup Of Suspected Hematological Malignancy.

BACKGROUND: Little attention has been given to the risk of cardiovascular and psychiatric comorbidities during the clinical evaluation of a suspected hematological malignancy. METHODS: Based on Skåne Healthcare Register, we performed a population-based cohort study of 1,527,449 individuals residing during 2005-2014 in Skåne, Sweden. We calculated the incidence rate ratios (IRRs) of cardiovascular diseases or psychiatric disorders during the diagnostic workup of 5495 patients with hematological malignancy and 18,906 individuals that underwent a bone marrow aspiration or biopsy or lymph node biopsy without receiving a diagnosis of any malignancy ("biopsied individuals"), compared to individuals without such experience (i.e., reference). RESULTS: There was a higher rate of cardiovascular diseases during the diagnostic workup of patients with hematological malignancy (overall IRR, 3.3; 95% CI, 2.9 to 3.8; greatest IRR for embolism and thrombosis, 8.1; 95% CI, 5.2 to 12.8) and biopsied individuals (overall IRR, 4.9; 95% CI, 4.6 to 5.3; greatest IRR for stroke, 37.5; 95% CI, 34.1 to 41.2), compared to reference. Similarly, there was a higher rate of psychiatric disorders during the diagnostic workup of patients with hematological malignancy (IRR, 2.1; 95% CI, 1.5 to 2.8) and biopsied individuals (IRR, 3.1; 95% CI, 2.9 to 3.4). The rate increases were greater around the time of diagnosis or biopsy, compared to thereafter, for both outcomes. CONCLUSION: There were higher rates of cardiovascular diseases and psychiatric disorders during the diagnostic workup of a suspected hematological malignancy, regardless of the final diagnosis.

Quality of care for the dying across different levels of palliative care development: A population-based cohort study.

BACKGROUND: There is a lack of knowledge about how the provision and availability of specialized palliative care relates to the quality of dying in hospital and community-based settings. AIM: We aimed to explore the quality of care during last week of life in relation to different levels of palliative care development. DESIGN: We investigated access to palliative care in Southern Sweden, where one region offers palliative care in accordance with European Association for Palliative Care guidelines for capacity, and the other region offers less developed palliative care. Data on approximately 12,000 deaths during 2015 were collected from the Swedish Register of Palliative Care. The quality of care was investigated by region, and was measured in terms of assessment of oral health and of pain, and end-of-life conversation, companionship at death and artificial nutrition/fluid in the last 24 h. RESULTS: The overall quality of care during last week of life was not consistently better in the region with fully developed palliative care compared with the less developed region. In fact, for patients dying in hospitals and community-based settings, the quality was statistically significantly better in the less developed region. The small proportion of patients who had access to specialized palliative care had superior quality of care during the last week of life as compared to patients in other care settings. CONCLUSION: The capacity of specialized palliative care does not per se influence the quality of care during the last week of life for patients in other settings.

Feasibility of reusing time-matched controls in an overlapping cohort.

The methods developed for secondary analysis of nested case-control data have been illustrated only in simplified settings in a common cohort and have not found their way into biostatistical practice. This paper demonstrates the feasibility of reusing prior nested case-control data in a realistic setting where a new outcome is available in an overlapping cohort where no new controls were gathered and where all data have been anonymised. Using basic information about the background cohort and sampling criteria, the new cases and prior data are "aligned" to identify the common underlying study base. With this study base, a Kaplan-Meier table of the prior outcome extracts the risk sets required to calculate the weights to assign to the controls to remove the sampling bias. A weighted Cox regression, implemented in standard statistical software, provides unbiased hazard ratios. Using the method to compare cases of contralateral breast cancer to available controls from a prior study of metastases, we identified a multifocal tumor as a risk factor that has not been reported previously. We examine the sensitivity of the method to an imperfect weighting scheme and discuss its merits and pitfalls to provide guidance for its use in medical research studies.