The CLL comorbidity index in a population-based cohort: a tool for clinical care and research.
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ABSTRACT:
SUBMITTER: Rotbain EC
PROVIDER: S-EPMC9043948 | biostudies-literature | 2022 Apr
REPOSITORIES: biostudies-literature
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The CLL comorbidity index in a population-based cohort: a tool for clinical care and research.
Rotbain Emelie C EC Gordon Max J MJ Vainer Noomi N Frederiksen Henrik H Hjalgrim Henrik H Danilov Alexey V AV Niemann Carsten U CU
Blood advances 20220401 8
The chronic lymphocytic leukemia comorbidity index (CLL-CI) is an efficient, CLL-specific tool derived from the Cumulative Illness Rating Scale. The CLL-CI is based on the assessment of the organ systems found to be most strongly associated with event-free survival (EFS) in CLL: vascular, upper gastrointestinal, and endocrine, at the time of initiation of CLL therapy. The CLL-CI categorizes patients into low, intermediate, and high risk groups. In the present study, we have employed the CLL-CI i ...[more]
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Project description:PurposeComorbid medical conditions define a subset of patients with chronic lymphocytic leukemia (CLL) with poor outcomes. However, which comorbidities are most predictive remains understudied.Experimental designWe conducted a retrospective analysis from 10 academic centers to ascertain the relative importance of comorbidities assessed by the cumulative illness rating scale (CIRS). The influence of specific comorbidities on event-free survival (EFS) was assessed in this derivation dataset using random survival forests to construct a CLL-specific comorbidity index (CLL-CI). Cox models were then fit to this dataset and to a single-center, independent validation dataset.ResultsThe derivation and validation sets comprised 570 patients (59% receiving Bruton tyrosine kinase inhibitor, BTKi) and 167 patients (50% receiving BTKi), respectively. Of the 14 CIRS organ systems, three had a strong and stable influence on EFS: any vascular, moderate/severe endocrine, moderate/severe upper gastrointestinal comorbidity. These were combined to create the CLL-CI score, which was categorized into 3 risk groups. In the derivation dataset, the median EFS values were 58, 33, and 20 months in the low, intermediate, and high-risk groups, correspondingly. Two-year overall survival (OS) rates were 96%, 91%, and 82%. In the validation dataset, median EFS values were 81, 40, and 23 months (two-year OS rates 97%/92%/88%), correspondingly. Adjusting for prognostic factors, CLL-CI was significantly associated with EFS in patients treated with either chemo-immunotherapy or with BTKi in each of our 2 datasets.ConclusionsThe CLL-CI is a simplified, CLL-specific comorbidity index that can be easily applied in clinical practice and correlates with survival in CLL.
| S-EPMC8416936 | biostudies-literature
Project description:BackgroundThe aim of this study was to assess the correlation between obstetric co-morbidity index (OBCMI) and severe maternal morbidity (SMM) in antepartum obstetrics transfers. By utilizing a population of transfers to a level IV maternal care facility, we hope to demonstrate validity for the use of OBCMI in the triage of transfer to provide risk-appropriate maternal care.MethodsAntepartum obstetrics transfers to a single level IV maternal care facility from 1/1/2016 to 12/31/2020 that resulted in delivery during the same encounter were included in this retrospective study. The components of the OBCMI score were retrospectively collected by manual chart review of transfer and admission notes in the electronic medical record (EMR). SMM was determined via ICD-10 and CPT code extraction from time of transfer through six weeks postpartum and confirmed by the same reviewer. Mode of delivery, length of stay, ICU admission, readmission and reoperation were obtained via institutional databases and manual EMR review.ResultsAmong 561 transfers meeting the inclusion criteria, the median OBCMI was significantly higher for transfers with a maternal-only indication (n = 232) compared to fetal-only( n = 282) (median [IQR], 6 [4-8], 5 [4-6], and 1 [0-2] for maternal-only, maternal-fetal combined (n = 47), and fetal-only; p < 0.001). The prevalence of SMM was 16.8% (39/232), 27.7% (13/47), 2.1% (6/282), p < 0.0001 for those transferred for maternal, fetal and maternal, and fetal only indications respectively. The median (IQR) OBCMI score was 5 (4-8) and 3 (1-5) for those with versus without SMM. A cut-off OBCMI score of ≥ 4 was identified with 81% sensitivity (95% CI 68.6-90.1%) in predicting SMM (P = < .0001) and was noted to be significantly associated with operative delivery, blood transfusion, ICU admission, prolonged hospitalization, and reoperation. Using a cut-off OBCMI score of ≥ 4 on the population transferred for maternal and maternal-fetal combined indications only (279) yielded a specificity of 90.4% and sensitivity of 23.8% (p = 0.024).ConclusionOBCMI was demonstrated to discriminate for SMM in a population of obstetrics transfers to a Level IV maternal care facility. When stratifying for maternal indicated transfers, the ability of OBCMI as a predictive tool decreased. The obtained cutoff OBCMI value of ≥ 4 had high specificity but may miss a significant population that would benefit from transfer. Use of the OBCMI may be too crude of a measure to provide a comprehensive risk assessment to predict SMM and adverse obstetrics outcomes. Further studies that may include newer tools such as machine learning may be necessary to develop a more clinically useful tool.
| S-EPMC11600594 | biostudies-literature
Project description:BackgroundWe report on the establishment of a web-based Cancer Epidemiology Descriptive Cohort Database (CEDCD). The CEDCD's goals are to enhance awareness of resources, facilitate interdisciplinary research collaborations, and support existing cohorts for the study of cancer-related outcomes.MethodsComprehensive descriptive data were collected from large cohorts established to study cancer as primary outcome using a newly developed questionnaire. These included an inventory of baseline and follow-up data, biospecimens, genomics, policies, and protocols. Additional descriptive data extracted from publicly available sources were also collected. This information was entered in a searchable and publicly accessible database. We summarized the descriptive data across cohorts and reported the characteristics of this resource.ResultsAs of December 2015, the CEDCD includes data from 46 cohorts representing more than 6.5 million individuals (29% ethnic/racial minorities). Overall, 78% of the cohorts have collected blood at least once, 57% at multiple time points, and 46% collected tissue samples. Genotyping has been performed by 67% of the cohorts, while 46% have performed whole-genome or exome sequencing in subsets of enrolled individuals. Information on medical conditions other than cancer has been collected in more than 50% of the cohorts. More than 600,000 incident cancer cases and more than 40,000 prevalent cases are reported, with 24 cancer sites represented.ConclusionsThe CEDCD assembles detailed descriptive information on a large number of cancer cohorts in a searchable database.ImpactInformation from the CEDCD may assist the interdisciplinary research community by facilitating identification of well-established population resources and large-scale collaborative and integrative research. Cancer Epidemiol Biomarkers Prev; 25(10); 1392-401. ©2016 AACR.
| S-EPMC5480970 | biostudies-literature
Project description:Comorbidity in myasthenia gravis (MG) is important for diagnosis, treatment and prognosis. Disease complexity was assessed by examining total drug treatment, immune therapy and comorbidity in a complete national MG cohort.All recipients of the MG-specific drug pyridostigmine 2004-2010 registered in the compulsory Norwegian Prescription Database who met the inclusion criteria were included. The pyridostigmine group was compared with the general Norwegian population.Myasthenia gravis patients received co-medication more often than the controls for nearly all groups of medication, including insulins (95% confidence interval 2.0-3.7), thyroid therapy (1.7-2.5), antidepressants (1.3-1.7), anti-infectives (1.2-1.4), lipid-modifying agents (1.1-1.4) and immunomodulating agents (6.8-8.8).Myasthenia gravis patients are more often treated with non-MG prescription drugs than controls, reflecting frequent co-medication and comorbidity.
| S-EPMC4238850 | biostudies-other
Project description:Background. Comorbidity is an important prognostic factor for survival in different cancers; however, neither the prevalence nor the impact of comorbidity has been investigated in bone sarcoma. Methods. All adult bone sarcoma patients from western Denmark treated at the Aarhus Sarcoma Centre in the period from 1979 to 2008 were identified through a validated population-based database. Charlson Comorbidity Index scores were computed, using discharge diagnoses from the Danish National Patient Registry. Survival was assessed as overall and disease-specific mortality. The impact of comorbidity was examined as rates according to the level of comorbidity as well as uni- and multivariately using proportional hazard models. Results. A total of 453 patients were identified. The overall prevalence of comorbidity was 19%. The prevalence increased with age and over the study period. In patients with Ewing/osteosarcoma, comorbidity was not associated with an increased overall or disease-specific mortality. However, patients with bone sarcomas other than Ewing/osteosarcoma had increased overall mortality. Independent prognostic factors for disease-specific survival were age, tumor size, stage at diagnosis, soft tissue involvement, grade, and surgery. Conclusion. The prevalence of comorbidity in bone sarcoma patients is low. Comorbidity impaired survival in patients with non-Ewing/nonosteosarcoma, histology. This emphasizes the importance of not only treating the sarcoma but also comorbidity.
| S-EPMC3958755 | biostudies-literature
Project description:BACKGROUND: It is unknown whether comorbidity interacts with colorectal cancer (CRC) to increase the rate of mortality beyond that explained by the independent effects of CRC and comorbid conditions. METHODS: We conducted a cohort study (1995-2010) of all Danish CRC patients (n=56963), and five times as many persons from the general population (n=271670) matched by age, gender, and specific comorbidities. To analyse comorbidity, we used the Charlson Comorbidity Index (CCI) scores. We estimated standardised mortality rates per 1000 person-years, and calculated interaction contrasts as a measure of the excess mortality rate not explained by the independent effects of CRC or comorbidities. RESULTS: Among CRC patients with a CCI score=1, the 0-1 year mortality rate was 415 out of 1000 person-years (95% confidence interval (CI): 401, 430) and the interaction accounted for 9.3% of this rate (interaction contrast=39 out of 1000 person-years, 95% CI: 22, 55). For patients with a CCI score of 4 or more, the interaction accounted for 34% of the mortality (interaction contrast=262 out of 1000 person-years, 95% CI: 215, 310). The interaction between CRC and comorbidities had limited influence on mortality beyond 1 year after diagnosis. CONCLUSION: Successful treatment of the comorbidity is pivotal and may reduce the mortality attributable to comorbidity itself, and also the mortality attributable to the interaction.
| S-EPMC3790187 | biostudies-other
Project description:ObjectivesAn obstetric comorbidity index has been developed recently with superior performance characteristics relative to general comorbidity measures in an obstetric population. This study aimed to externally validate this index and to examine the impact of including hospitalisation/delivery records only when estimating comorbidity prevalence and discriminative performance of the obstetric comorbidity index.DesignValidation study.SettingAlberta, Canada.PopulationPregnant women who delivered a live or stillborn infant in hospital (n = 5995).MethodsAdministrative databases were linked to create a population-based cohort. Comorbid conditions were identified from diagnoses for the delivery hospitalisation, all hospitalisations and all healthcare contacts (i.e. hospitalisations, emergency room visits and physician visits) that occurred during pregnancy and 3 months pre-conception. Logistic regression was used to test the discriminative performance of the comorbidity index.Main outcome measuresMaternal end-organ damage and extended length of stay for delivery.ResultsAlthough prevalence estimates for comorbid conditions were consistently lower in delivery records and hospitalisation data than in data for all healthcare contacts, the discriminative performance of the comorbidity index was constant for maternal end-organ damage [all healthcare contacts area under the receiver operating characteristic curve (AUC) = 0.70; hospitalisation data AUC = 0.67; delivery data AUC = 0.65] and extended length of stay for delivery (all healthcare contacts AUC = 0.60; hospitalisation data AUC = 0.58; delivery data AUC = 0.58).ConclusionsThe obstetric comorbidity index shows similar performance characteristics in an external population and is a valid measure of comorbidity in an obstetric population. Furthermore, the discriminative performance of the comorbidity index was similar for comorbidities ascertained at the time of delivery, in hospitalisation data or through all healthcare contacts.
| S-EPMC5006847 | biostudies-literature
Project description:BackgroundThe presence of comorbidity affects the care of cancer patients, many of whom are living with multiple comorbidities. The prevalence of cancer comorbidity, beyond summary metrics, is not well known. This study aims to estimate the prevalence of comorbid conditions among cancer patients in England, and describe the association between cancer comorbidity and socio-economic position, using population-based electronic health records.MethodsWe linked England cancer registry records of patients diagnosed with cancer of the colon, rectum, lung or Hodgkin lymphoma between 2009 and 2013, with hospital admissions records. A comorbidity was any one of fourteen specific conditions, diagnosed during hospital admission up to 6 years prior to cancer diagnosis. We calculated the crude and age-sex adjusted prevalence of each condition, the frequency of multiple comorbidity combinations, and used logistic regression and multinomial logistic regression to estimate the adjusted odds of having each condition and the probability of having each condition as a single or one of multiple comorbidities, respectively, by cancer type.ResultsComorbidity was most prevalent in patients with lung cancer and least prevalent in Hodgkin lymphoma patients. Up to two-thirds of patients within each of the four cancer patient cohorts we studied had at least one comorbidity, and around half of the comorbid patients had multiple comorbidities. Our study highlighted common comorbid conditions among the cancer patient cohorts. In all four cohorts, the odds of having a comorbidity and the probability of multiple comorbidity were consistently highest in the most deprived cancer patients.ConclusionsCancer healthcare guidelines may need to consider prominent comorbid conditions, particularly to benefit the prognosis of the most deprived patients who carry the greater burden of comorbidity. Insight into patterns of cancer comorbidity may inform further research into the influence of specific comorbidities on socio-economic inequalities in receipt of cancer treatment and in short-term mortality.
| S-EPMC6986047 | biostudies-literature
Project description:Dementia is one of the most burdensome illnesses in elderly populations worldwide. However, the literature about multiple risk factors for dementia is scant.To develop a simple, rapid, and appropriate predictive tool for the clinical quantitative assessment of multiple risk factors for dementia.A population-based cohort study.Based on the Taiwan National Health Insurance Research Database, participants first diagnosed with dementia from 2000 to 2009 and aged ?65 years in 2000 were included.A logistic regression model with Bayesian supervised learning inference was implemented to evaluate the quantitative effects of 1- to 6-comorbidity risk factors for dementia in the elderly Taiwanese population: depression, vascular disease, severe head injury, hearing loss, diabetes mellitus (DM), and senile cataract, identified from a nationwide longitudinal population-based database.This study enrolled 4749 (9.5%) patients first diagnosed as having dementia. Aged, female, urban residence, and low income were found as independent sociodemographic risk factors for dementia. Among all odds ratios (ORs) of 2-comorbidity risk factors for dementia, comorbid depression and vascular disease had the highest adjusted OR of 6.726. The 5-comorbidity risk factors, namely depression, vascular disease, severe head injury, hearing loss, and DM, exhibited the highest OR of 8.767. Overall, the quantitative effects of 2 to 6 comorbidities and age difference on dementia gradually increased; hence, their ORs were less than additive. These results indicate that depression is a key comorbidity risk factor for dementia.The present findings suggest that physicians should pay more attention to the role of depression in dementia development. Depression is a key cormorbidity risk factor for dementia. It is the urgency of evaluating the nature of the link between depression and dementia; and further testing what extent controlling depression could effectively lead to the prevention of dementia.
| S-EPMC5908585 | biostudies-literature
Project description:BackgroundAn increased fracture risk has been described as a complication of Type 2 diabetes mellitus (T2DM). Clinical prediction models for general population have a limited predictive accuracy for fractures in T2DM patients. The aim was to develop and validate a clinical prediction tool for the estimation of 5-year hip and major fracture risk in T2DM patients.Methods and resultsA cohort of newly diagnosed T2DM patients (n = 51,143, aged 50-85, 57% men) was extracted from the Information System for the Development of Research in Primary Care (SIDIAP) database, containing computerized primary care records for >80% of the population of Catalonia, Spain (>6 million people). Patients were followed up from T2DM diagnosis until the earliest of death, transfer out, fracture, or end of study. Cox proportional hazards regression was used to model the 5-year risk of hip and major fracture. Calibration and discrimination were assessed. Hip and major fracture incidence rates were 1.84 [95%CI 1.64 to 2.05] and 7.12 [95%CI 6.72 to 7.53] per 1,000 person-years, respectively. Both hip and major fracture prediction models included age, sex, previous major fracture, statins use, and calcium/vitamin D supplements; previous ischemic heart disease was also included for hip fracture and stroke for major fracture. Discrimination (0.81 for hip and 0.72 for major fracture) and calibration plots support excellent internal validity.ConclusionsThe proposed prediction models have good discrimination and calibration for the estimation of both hip and major fracture risk in incident T2DM patients. These tools incorporate key T2DM macrovascular complications generally available in primary care electronic medical records, as well as more generic fracture risk predictors. Future work will focus on validation of these models in external cohorts.
| S-EPMC6128577 | biostudies-literature