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OBJECTIVE: No previous study examined impact of dementia in the outcome of allogeneic hematopoietic stem cell transplantation (HSCT). We aimed to investigate overall survival (OS) of patients with dementia after receiving HSCT. METHODS: Among 8,230 patients who underwent HSCT between 2002 and 2018, 5,533 patients younger than 50 years were first excluded. Remaining patients were divided into those who were and were not diagnosed with dementia before HSCT (dementia group: n = 31; no dementia: n = 2,666). Thereafter, among 2,666 participants without dementia, 93 patients were selected via propensity-matched score as non-dementia group. Patients were followed from the day they received HSCT to the occurrence of death or the last follow-up day (December 31, 2018), whichever came first. RESULTS: With median follow-up of 621 days for dementia group and 654 days for non-dementia group, 2 year-OS of dementia group was lower than that of non-dementia group (53.3% [95% confidence interval, 95% CI, 59.0-80.2%] vs. 68.8% [95% CI, 38.0-68.2%], p = 0.076). In multivariate analysis, dementia had significant impacts on OS (hazard risk = 2.539, 95% CI, 1.166-4.771, p = 0.017). CONCLUSION: Our results indicated that patients diagnosed with dementia before HSCT have 2.539 times higher risk of mortality after transplantation than those not having dementia. With number of elderly needing HSCT is increasing, further work to establish treatment guidelines for the management of HSCT in people with dementia is needed.
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BACKGROUND: As the COVID-19 pandemic continues, an initial risk-adapted allocation is crucial for managing medical resources and providing intensive care. OBJECTIVE: In this study, we aimed to identify factors that predict the overall survival rate for COVID-19 cases and develop a COVID-19 prognosis score (COPS) system based on these factors. In addition, disease severity and the length of hospital stay for patients with COVID-19 were analyzed. METHODS: We retrospectively analyzed a nationwide cohort of laboratory-confirmed COVID-19 cases between January and April 2020 in Korea. The cohort was split randomly into a development cohort and a validation cohort with a 2:1 ratio. In the development cohort (n=3729), we tried to identify factors associated with overall survival and develop a scoring system to predict the overall survival rate by using parameters identified by the Cox proportional hazard regression model with bootstrapping methods. In the validation cohort (n=1865), we evaluated the prediction accuracy using the area under the receiver operating characteristic curve. The score of each variable in the COPS system was rounded off following the log-scaled conversion of the adjusted hazard ratio. RESULTS: Among the 5594 patients included in this analysis, 234 (4.2%) died after receiving a COVID-19 diagnosis. In the development cohort, six parameters were significantly related to poor overall survival: older age, dementia, chronic renal failure, dyspnea, mental disturbance, and absolute lymphocyte count <1000/mm3. The following risk groups were formed: low-risk (score 0-2), intermediate-risk (score 3), high-risk (score 4), and very high-risk (score 5-7) groups. The COPS system yielded an area under the curve value of 0.918 for predicting the 14-day survival rate and 0.896 for predicting the 28-day survival rate in the validation cohort. Using the COPS system, 28-day survival rates were discriminatively estimated at 99.8%, 95.4%, 82.3%, and 55.1% in the low-risk, intermediate-risk, high-risk, and very high-risk groups, respectively, of the total cohort (P<.001). The length of hospital stay and disease severity were directly associated with overall survival (P<.001), and the hospital stay duration was significantly longer among survivors (mean 26.1, SD 10.7 days) than among nonsurvivors (mean 15.6, SD 13.3 days). CONCLUSIONS: The newly developed predictive COPS system may assist in making risk-adapted decisions for the allocation of medical resources, including intensive care, during the COVID-19 pandemic.
