Dataset Information

Prediction of Unplanned Hospitalizations in Older Patients Treated with Chemotherapy

ABSTRACT:

Simple Summary

Unplanned hospitalizations (UHs) are common among elderly patients with cancer who receive chemotherapy. This fact decreases quality of life or performance status and increases health costs. Our objective was to determine predictive factors for UH in this population. A score based on six variables taken from geriatric assessment and chemotherapy characteristics was developed in a series of 493 elderly patients receiving chemotherapy. The use of this score may reliably identify patients at risk for UH, thus helping to plan treatment, implement adaptive measures, and set up a close follow-up schedule.

Abstract

Purpose: To determine the incidence of unplanned hospitalization (UH) and to identify risk factors for UH in elderly patients with cancer who start chemotherapy. Methods: In all, 493 patients over 70 years starting new chemotherapy regimens were prospectively included. A pre-chemotherapy geriatric assessment was performed, and tumor and treatment variables were collected. The association between these factors and UH was examined by using multivariable logistic regression. Score points were assigned to each risk factor. Results: During the first 6 months of treatment, 37% of patients had at least one episode of UH. Risk factors were the use of combination chemotherapy at standard doses, a MAX2 index ≥1, a Charlson comorbidity score ≥2, albumin level <3.5 g/dL, falls in the past 6 months ≥1, and weight loss >5%. Three risk groups for UH were established according to the score in all patients: 0–1: 17.5%; 2: 34%; and 3–7: 57% (p < 0.001). The area under receiver operation characteristic (ROC) curve was 0.72 (95% CI: 0.67–0.77). Conclusion: This simple tool can help to reduce the incidence of UH in elderly patients with cancer who are scheduled to initiate chemotherapy treatment.

SUBMITTER: Feliu J

PROVIDER: S-EPMC8004134 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Geriatric assessment (GA) is an important tool for management of older cancer patients; however, GA research has been performed primarily in the outpatient setting. The primary objective of this study was to determine feasibility of GA during an unplanned hospital stay. Secondary objectives were to describe deficits found with GA, to assess whether clinicians recognized and addressed deficits, and to determine 30-day readmission rates.The study was designed as an extension of an existing registry, "Carolina Senior: Registry for Older Patients." Inclusion criteria were age 70 and older and biopsy-proven solid tumor, myeloma, or lymphoma. Patients had to complete the GA within 7 days of nonelective admission to University of North Carolina Hospital.A total of 142 patients were approached, and 90 (63%) consented to participation. All sections of GA had at least an 83% completion rate. Overall, 53% of patients reported problems with physical function, 63% had deficits in instrumental activities of daily living, 34% reported falls, 12% reported depression, 31% had ?10% weight loss, and 12% had abnormalities in cognition. Physician documentation of each deficit ranged from 20% to 46%. Rates of referrals to allied health professionals were not significantly different between patients with and without deficits. The 30-day readmission rate was 29%.GA was feasible in this population. Hospitalized older cancer patients have high levels of functional and psychosocial deficits; however, clinician recognition and management of deficits were poor. The use of GA instruments to guide referrals to appropriate services is a way to potentially improve outcomes in this vulnerable population.Geriatric assessment (GA) is an important tool in the management of older cancer patients; however, its primary clinical use has been in the outpatient setting. During an unplanned hospitalization, patients are extremely frail and are most likely to benefit from GA. This study demonstrates that hospitalized older adults with cancer have high levels of functional deficits on GA. These deficits are under-recognized and poorly managed by hospital-based clinicians in a tertiary care setting. Incorporation of GA measures during a hospital stay is a way to improve outcomes in this population.

Project description:BackgroundDue to ageing of the population the incidence of multimorbidity and polypharmacy is rising. Polypharmacy is a risk factor for medication-related (re)admission and therefore places a significant burden on the healthcare system. The reported incidence of medication-related (re)admissions varies widely due to the lack of a clear definition. Some medications are known to increase the risk for medication-related admission and are therefore published in the triggerlist of the Dutch guideline for Polypharmacy in older patients. Different interventions to support medication optimization have been studied to reduce medication-related (re)admissions. However, the optimal template of medication optimization is still unknown, which contributes to the large heterogeneity of their effect on hospital readmissions. Therefore, we implemented a clinical decision support system (CDSS) to optimize medication lists and investigate whether continuous use of a CDSS reduces the number of hospital readmissions in older patients, who previously have had an unplanned probably medication-related hospitalization.MethodsThe CHECkUP study is a multicentre randomized study in older (≥60 years) patients with an unplanned hospitalization, polypharmacy (≥5 medications) and using at least two medications from the triggerlist, from Zuyderland Medical Centre and Maastricht University Medical Centre+ in the Netherlands. Patients will be randomized. The intervention consists of continuous (weekly) use of a CDSS, which generates a Medication Optimization Profile, which will be sent to the patient's general practitioner and pharmacist. The control group will receive standard care. The primary outcome is hospital readmission within 1 year after study inclusion. Secondary outcomes are one-year mortality, number of emergency department visits, nursing home admissions, time to hospital readmissions and we will evaluate the quality of life and socio-economic status.DiscussionThis study is expected to add evidence on the knowledge of medication optimization and whether use of a continuous CDSS ameliorates the risk of adverse outcomes in older patients, already at an increased risk of medication-related (re)admission. To our knowledge, this is the first large study, providing one-year follow-up data and reporting not only on quality of care indicators, but also on quality-of-life.Trial registrationThe trial was registered in the Netherlands Trial Register on October 14, 2018, identifier: NL7449 (NTR7691). https://www.trialregister.nl/trial/7449 .

Project description:BackgroundIdentification of community-dwelling older adults at risk of unplanned hospitalizations is of importance to facilitate preventive interventions. Our objective was to review and appraise the methodological quality and predictive performance of prediction models for predicting unplanned hospitalizations in community-dwelling older adults.Methods and findingsWe searched MEDLINE, EMBASE and CINAHL from August 2013 to January 2021. Additionally, we checked references of the identified articles for the inclusion of relevant publications and added studies from two previous reviews that fulfilled the eligibility criteria. We included prospective and retrospective studies with any follow-up period that recruited adults aged 65 and over and developed a prediction model predicting unplanned hospitalizations. We included models with at least one (internal or external) validation cohort. The models had to be intended to be used in a primary care setting. Two authors independently assessed studies for inclusion and undertook data extraction following recommendations of the CHARMS checklist, while quality assessment was performed using the PROBAST tool. A total of 19 studies met the inclusion criteria. Prediction horizon ranged from 4.5 months to 4 years. Most frequently included variables were specific medical diagnoses (n = 11), previous hospital admission (n = 11), age (n = 11), and sex or gender (n = 8). Predictive performance in terms of area under the curve ranged from 0.61 to 0.78. Models developed to predict potentially preventable hospitalizations tended to have better predictive performance than models predicting hospitalizations in general. Overall, risk of bias was high, predominantly in the analysis domain.ConclusionsModels developed to predict preventable hospitalizations tended to have better predictive performance than models to predict all-cause hospitalizations. There is however substantial room for improvement on the reporting and analysis of studies. We recommend better adherence to the TRIPOD guidelines.

Project description:Infection is an important cause of hospitalization and death in patients receiving dialysis. Few studies have examined the full range of infections experienced by dialysis patients. The purpose of this study is to examine types, rates, and risk factors for infection in older persons starting dialysis therapy.Retrospective observational cohort study.The cohort was assembled from the US Renal Data System and included patients aged 65-100 years who initiated dialysis therapy between January 1, 2000, and December 31, 2002. Exclusions included prior kidney transplant, unknown dialysis modality, or death, loss to follow-up, or transplant during the first 90 days of dialysis therapy. Patients were followed up until death, transplant, or study end on December 31, 2004.Baseline demographics, comorbid conditions, and serum albumin and hemoglobin levels.Infection-related hospitalizations were ascertained using discharge International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes. Hospitalization rates were calculated for each type of infection. The Wei-Lin-Weissfeld model was used to examine risk factors for up to 4 infection-related events.119,858 patients were included, 7,401 of whom were on peritoneal dialysis therapy. During a median follow-up of 1.9 years, infection-related diagnoses were observed in approximately 35% of all hospitalizations. Approximately 50% of patients had at least 1 infection-related hospitalization. Rates (per 100 person-years) of pulmonary, soft-tissue, and genitourinary infections ranged from 8.3-10.3 in patients on peritoneal dialysis therapy and 10.2-15.3 in patients on hemodialysis therapy. Risk factors for infection included older age, female sex, diabetes, heart failure, pulmonary disease, and low serum albumin level.Use of ICD-9-CM codes, reliance on Medicare claims to capture hospitalizations, use of the Medical Evidence Form to ascertain comorbid conditions, and absence of data for dialysis access.Infection-related hospitalization is frequent in older patients on dialysis therapy. A broad range of infections, many unrelated to dialysis access, result in hospitalization in this population.

Dataset Information

Prediction of Unplanned Hospitalizations in Older Patients Treated with Chemotherapy

Simple Summary

Abstract

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets