bims-minfam Biomed News
on Inflammation and metabolism in ageing and cancer
Issue of 2023‒01‒01
eight papers selected by
Ayesh Seneviratne
Western University


  1. Aging (Albany NY). 2022 Dec 26. 14
      
    Keywords:  aging; epigenetics; healthspan; longevity; transient reprogramming
    DOI:  https://doi.org/10.18632/aging.204457
  2. Nat Cancer. 2022 Dec 29.
      Acute myeloid leukemia (AML) is a hematopoietic malignancy with poor prognosis and limited treatment options. Here we provide a comprehensive census of the bone marrow immune microenvironment in adult and pediatric patients with AML. We characterize unique inflammation signatures in a subset of AML patients, associated with inferior outcomes. We identify atypical B cells, a dysfunctional B-cell subtype enriched in patients with high-inflammation AML, as well as an increase in CD8+GZMK+ and regulatory T cells, accompanied by a reduction in T-cell clonal expansion. We derive an inflammation-associated gene score (iScore) that associates with poor survival outcomes in patients with AML. Addition of the iScore refines current risk stratifications for patients with AML and may enable identification of patients in need of more aggressive treatment. This work provides a framework for classifying patients with AML based on their immune microenvironment and a rationale for consideration of the inflammatory state in clinical settings.
    DOI:  https://doi.org/10.1038/s43018-022-00480-0
  3. Front Med (Lausanne). 2022 ;9 1060990
      Background: Frailty has been increasingly recognized as a public health problem for aging populations with significant social impact, particularly in low- and middle-income countries. We aimed to develop a modified version of the Thai Frailty Index (TFI) and explore the association between different frailty statuses, socioeconomic factors, and mortality in community-dwelling older people from a middle-income country.Methods: The data from participants aged ≥60 years in the Fourth Thai National Health Examination Survey were used to construct the 30-item TFI. Cutoff points were created based on stratum-specific likelihood ratio. TFI ≤ 0.10 was categorized as fit, 0.10-0.25 as pre-frail, 0.25-0.45 as mildly frail, and >0.45 as severely frail. The association of frailty status with mortality was examined using Cox proportional hazard models.
    Findings: Among 8,195 older adults with a mean age of 69.2 years, 1,284 died during the 7-year follow-up. The prevalence of frailty was 16.6%. The adjusted hazard ratio (aHR) for mortality in pre-frail was 1.76 (95% CI = 1.50-2.07), mildly frail 2.79 (95% CI = 2.33-3.35), and severely frail 6.34 (95% CI = 4.60-8.73). Having a caretaker in the same household alleviated mortality risk for severely frail participants with an aHR of 2.93 (95% CI = 1.92-4.46) compared with an aHR of 6.89 (95% CI = 3.87-12.26) among those living without a caretaker.
    Interpretation: The severity of frailty classified by the modified TFI can predict long-term mortality risk for community-dwelling older adults. Identification of severely frail older people to provide appropriate care might alleviate mortality risk. Our findings can inform policymakers to appropriately allocate services in a resource-limited setting.
    Keywords:  Thailand; caretaker; frailty; mortality risk; older
    DOI:  https://doi.org/10.3389/fmed.2022.1060990
  4. Am J Cardiol. 2022 Dec 22. pii: S0002-9149(22)01235-8. [Epub ahead of print]190 75-81
      Frailty is associated with adverse outcomes in heart failure (HF). A parsimonious frailty index (FI) that predicts outcomes of older, multimorbid patients with HF could be a useful resource for clinicians. A retrospective study of veterans hospitalized from October 2015 to October 2018 with HF, aged ≥50 years, and discharged home developed a 10-item parsimonious FI using machine learning from diagnostic codes, laboratory results, vital signs, and ejection fraction (EF) from outpatient encounters. An unsupervised clustering technique identified 5 FI strata: severely frail, moderately frail, mildly frail, prefrail, and robust. We report hazard ratios (HRs) of mortality, adjusting for age, gender, race, and EF and odds ratios (ORs) for 30-day and 1-year emergency department visits and all-cause hospitalizations after discharge. We identified 37,431 veterans (age, 73 ± 10 years; co-morbidity index, 5 ± 3; 43.5% with EF ≤40%). All frailty groups had a higher mortality than the robust group: severely frail (HR 2.63, 95% confidence interval [CI] 2.42 to 2.86), moderately frail (HR 2.04, 95% CI 1.87 to 2.22), mildly frail (HR 1.60, 95% CI 1.47 to 1.74), and prefrail (HR 1.18, 95% CI: 1.07 to 1.29). The associations between frailty and mortality remained unchanged in the stratified analysis by age or EF. The combined (severely, moderately, and mildly) frail group had higher odds of 30-day emergency visits (OR 1.62, 95% CI 1.43 to 1.83), all-cause readmission (OR, 1.75, 95% CI 1.52 to 2.02), 1-year emergency visits (OR 1.70, 95% CI 1.53 to 1.89), rehospitalization (OR 2.18, 95% CI 1.97 to 2.41) than the robust group. In conclusion, a 10-item FI is associated with postdischarge outcomes among patients discharged home after a hospitalization for HF. A parsimonious FI may aid clinical prediction at the point of care.
    DOI:  https://doi.org/10.1016/j.amjcard.2022.11.044
  5. Ann Intensive Care. 2022 Dec 31. 12(1): 120
      BACKGROUND: While frailty is a known predictor of adverse outcomes in older patients, its effect in younger populations is unknown. This prospective observational study was conducted in a tertiary-level mixed ICU to assess the impact of frailty on long-term survival in intensive care patients of different ages.METHODS: Data on premorbid frailty (Clinical Frailty Score; CFS), severity of illness (the Simplified Acute Physiology Score, third version; SAPS3), limitations of care and outcome were collected in 817 adult ICU patients. Hazard ratios (HR) for death within 180 days after ICU admission were calculated. Unadjusted and adjusted analyses were used to evaluate the association of frailty with outcome in different age groups.
    RESULTS: Patients were classified into predefined age groups (18-49 years (n = 241), 50-64 (n = 188), 65-79 (n = 311) and 80 years or older (n = 77)). The proportion of frail (CFS ≥ 5) patients was 41% (n = 333) in the overall population and increased with each age strata (n = 46 (19%) vs. n = 67 (36%) vs. n = 174 (56%) vs. n = 46 (60%), P < 0.05). Frail patients had higher SAPS3, more treatment restrictions and higher ICU mortality. Frailty was associated with an increased risk of 180-day mortality in all age groups (HR 5.7 (95% CI 2.8-11.4), P < 0.05; 8.0 (4.0-16.2), P < 0.05; 4.1 (2.2-6.6), P < 0.05; 2.4 (1.1-5.0), P = 0.02). The effect remained significant after adjustment for SAPS3, comorbidity and limitations of treatment only in patients aged 50-64 (2.1 (1.1-3.1), P < 0.05).
    CONCLUSIONS: Premorbid frailty is common in ICU patients of all ages and was found in 55% of patients aged under 64 years. Frailty was independently associated with mortality only among middle-aged patients, where the risk of death was increased twofold. Our study supports the use of frailty assessment in identifying younger ICU patients at a higher risk of death.
    Keywords:  Critical illness; Frailty; Intensive care unit; Outcome
    DOI:  https://doi.org/10.1186/s13613-022-01098-2
  6. Ageing Res Rev. 2022 Dec 21. pii: S1568-1637(22)00274-4. [Epub ahead of print]84 101832
      Caring for the elderly has always been challenging for the intensive care unit (ICU) physician. Concerns like frailty, comorbidities, polypharmacy and advanced directives come up even before admission into the unit. The COVID-19 pandemic has put forward a variety of issues concerning elderly populations, making the topic more relevant than ever. Admittance to the ICU, an unequivocally multifactorial decision, requires special consideration from the side of the physician when caring for an elderly person. Patients' wishes are to be respected and thus given priority. Triage assessment must also account for age-related physiological alterations and functional status. Once in the ICU, special attention should be given to age-related specificities, such as therapeutic interventions' controversial role, infection susceptibility, and post-operative care, that could potentially alter the course of hospitalization and affect outcomes. Following ICU discharge, ensuring proper rehabilitation for both survivors and their caregivers can improve long-term outcomes and subsequent quality of life. The pandemic and its implications may limit the standard of care for the elderly requiring ICU support. Socioeconomic factors that further perplex the situation must be addressed. Elderly patients currently represent a vast expanding population in ICU. Tailoring safe treatment plans to match patients' wishes, and personalized needs will guide critical care for the elderly from this time forward.
    Keywords:  Aged; Aging; Critical care; Critically ill; Frail elderly; Intensive care unit
    DOI:  https://doi.org/10.1016/j.arr.2022.101832
  7. JAMA Oncol. 2022 Dec 29.
      Importance: Patients with cancer are known to have increased risk of COVID-19 complications, including death.Objective: To determine the association of COVID-19 vaccination with breakthrough infections and complications in patients with cancer compared to noncancer controls.
    Design, Setting, and Participants: Retrospective population-based cohort study using linked administrative databases in Ontario, Canada, in residents 18 years and older who received COVID-19 vaccination. Three matched groups were identified (based on age, sex, type of vaccine, date of vaccine): 1:4 match for patients with hematologic and solid cancer to noncancer controls (hematologic and solid cancers separately analyzed), 1:1 match between patients with hematologic and patients with solid cancer.
    Exposures: Cancer diagnosis.
    Main Outcomes and Measures: Outcomes occurring 14 days after receipt of second COVID-19 vaccination dose: primary outcome was SARS-CoV-2 breakthrough infection; secondary outcomes were emergency department visit, hospitalization, and death within 4 weeks of SARS-CoV-2 infection (end of follow-up March 31, 2022). Multivariable cumulative incidence function models were used to obtain adjusted hazard ratio (aHR) and 95% CIs.
    Results: A total of 289 400 vaccinated patients with cancer (39 880 hematologic; 249 520 solid) with 1 157 600 matched noncancer controls were identified; the cohort was 65.4% female, and mean (SD) age was 66 (14.0) years. SARS-CoV-2 breakthrough infection was higher in patients with hematologic cancer (aHR, 1.33; 95% CI, 1.20-1.46; P < .001) but not in patients with solid cancer (aHR, 1.00; 95% CI, 0.96-1.05; P = .87). COVID-19 severe outcomes (composite of hospitalization and death) were significantly higher in patients with cancer compared to patients without cancer (aHR, 1.52; 95% CI, 1.42-1.63; P < .001). Risk of severe outcomes was higher among patients with hematologic cancer (aHR, 2.51; 95% CI, 2.21-2.85; P < .001) than patients with solid cancer (aHR, 1.43; 95% CI, 1.24-1.64; P < .001). Patients receiving active treatment had a further heightened risk for COVID-19 severe outcomes, particularly those who received anti-CD20 therapy. Third vaccination dose was associated with lower infection and COVID-19 complications, except for patients receiving anti-CD20 therapy.
    Conclusions and Relevance: In this large population-based cohort study, patients with cancer had greater risk of SARS-CoV-2 infection and worse outcomes than patients without cancer, and the risk was highest for patients with hematologic cancer and any patients with cancer receiving active treatment. Triple vaccination was associated with lower risk of poor outcomes.
    DOI:  https://doi.org/10.1001/jamaoncol.2022.6815