Lancet Healthy Longevity最新文献

Mortality risk prediction models can support decision making in older adults with cancer; however, existing models are associated with a high risk of bias. This systematic review assessed published prediction models for overall and all-cause mortality in adults with cancer aged 65 years or older. We searched for publications in Ovid Embase, Ovid Medline, Cochrane CENTRAL, and EBSCO CINAHL on Nov 25, 2022, and updated the search on Feb 24, 2024. We included 250 studies, of which 182 (72·8%) reported both model development and internal validation. 176 (70·4%) of 250 models predicted overall survival; 40 (16·0%) models focused on lung cancer and 30 (12·0%) models on colorectal cancer. 43 (17·2%) models were specifically developed for older adults; 138 (55·2%) models did not incorporate geriatric variables such as comorbidities, nutrition, and cognition. Risk of bias was high in all models, largely owing to inappropriate handling of continuous predictors, univariable selection of predictors, and inadequate control for overfitting. These limitations preclude clinical use. Future models predicting overall and all-cause mortality in older adults with cancer should adhere to existing methodological guidelines and incorporate geriatric domains.

Diuretics are widely used as first-line therapy for heart failure and hypertension in older adults, but long-term continuation without a clear indication can increase adverse drug events such as electrolyte disturbances, renal dysfunction, hypotension, syncope, falls, and reduced quality of life-especially in people with multimorbidity, frailty, and polypharmacy. In this systematic review of international clinical practice guidelines and expert tools published up to August, 2025, we identified 41 resources (14 guidelines, 27 tools) and synthesised 184 unique recommendations on inappropriate chronic diuretic use and deprescribing. We searched Ovid MEDLINE and Embase using predefined concepts for heart failure, hypertension, clinical practice guidelines, and deprescribing. We included English-language guidelines and deprescribing tools for adults published after October, 2013, that addressed inappropriate chronic diuretic use or deprescribing. Deprescribing guidance was comparatively sparse and most often framed as prompts to consider stopping rather than practical how-to pathways. Only 16 recommendations offered actionable support (eg, stepwise tapering or discontinuation, monitoring and safety-netting, or usable algorithms or flowcharts). Consolidated, implementation-ready deprescribing guidance is urgently needed to support safer long-term diuretic management and shared decision making.

Background: Cataract remains the leading cause of blindness globally, which substantially affects quality of life and economic productivity. Despite being a highly cost-effective intervention, cataract surgery remains inaccessible to many, especially in low-resource settings. This study presents a dynamic model that aims to estimate the number of people who will die before receiving cataract surgery, using Kenya as a case study.

Methods: We developed a dynamic simulation model to project the national cataract backlog, surgical interventions, and mortality over a 50-year period (1990-2040). The model integrates demographic and epidemiological data, alongside key parameters including age-specific cataract incidence, severity progression, mortality risk, and surgical throughput. Sensitivity analysis was done to estimate the effect of different cataract surgical rates.

Findings: At current surgical capacity, the model estimates that 280 400 (77%) of 360 000 individuals on Kenya's cataract backlog in 2025 will die before receiving surgery, with 236 400 (66%) dying before 2030. Sensitivity analysis shows that doubling cataract surgical rates could enable an additional 24 000 people to receive treatment before death, representing a 16% reduction in untreated mortality. A ten-fold increase (cataract surgical rates of 7020 surgeries per million people per year) would nearly eliminate deaths among those awaiting surgery.

Interpretation: This model provides a comprehensive view of the national cataract burden by incorporating incidence, surgical capacity, and mortality estimates for untreated cases. It underscores the urgent need for expanded cataract surgery capacity and improved access to care. The model offers actionable insights for policy makers and health system planners aiming to reduce avoidable blindness and prevent premature deaths from treatable conditions.

Funding: The Wellcome Trust and Fred Hollows Foundation.

Background: Cerebral small vessel disease and alterations in retinal vascular calibre (RVC) are recognised precursors of stroke, dementia, and cognitive decline. We aimed to assess the effect of low-dose aspirin on white matter hyperintensity (WMH), a marker of cerebral small vessel disease, and changes in RVC.

Methods: We conducted a prospectively planned exploratory neurovascular substudy (ENVIS-ion) of the Aspirin in Reducing Events in the Elderly (ASPREE) double-blinded randomised clinical trial of 19 114 older adults (aged ≥70 years), who had no previous cardiovascular disease, stroke, or cognitive impairment at baseline. Participants were allocated to daily enteric-coated aspirin 100 mg or matching placebo using computer-generated randomisation and underwent MRI of the brain and fundus photography at two clinical trials sites in Australia at baseline and after 3 years. WMH and RVC measures were assessed by graders blinded to study treatment allocation. The effects of aspirin on total and regional WMH volumes (as a percentage of total brain volume) and RVC over time were analysed using linear models. ASPREE is registered with ClinicalTrials.gov, NCT01038583, and the International Standard Randomised Controlled Trial Number Registry, ISRCTN83772183.

Findings: Between April, 2010, and April, 2012, 610 participants from the eligible ASPREE cohort of 2346 individuals were enrolled in the ENVIS-ion substudy. Of the 610 participants (mean age 75·2 years [SD 4·1], 289 [47%] male and 321 [53%] female), 312 were assigned to receive aspirin and 298 to placebo. Over 3 years, the aspirin group had a greater increase in the percentage of deep WMH (β 0·14 [95% CI 0·01 to 0·27]) but there was no difference between aspirin and placebo groups in changes from baseline to 3 years in total brain WMH (0·05 [-0·02 to 0·11]) or periventricular WMH (0·03 [-0·03 to 0·09]). There was no evidence of an aspirin effect on RVC. The rate of major haemorrhage was higher in the aspirin arm for the ASPREE study (hazard ratio 1·38, 95% CI 1·18 to 1·62).

Interpretation: In this exploratory study, there was no evidence that low-dose aspirin in healthy older adults had any effect on RVC or attenuated the progression of WMH during a 3-year period.

Funding: National Health and Medical Research Council of Australia.

Background: Incidental findings are often found in imaging research, especially in older people (aged ≥75 years). Understanding their prevalence is essential to inform consent and disclosure protocols as well as anticipate onward investigation balanced against minimising unnecessary anxiety and health-care burden. The aim of this study was to determine the prevalence of incidental findings in a population-based sample of individuals aged 75-77 years using cardiovascular magnetic resonance (CMR) imaging and to inform duty-of-care frameworks for their reporting.

Methods: MyoFit46 was a prospective imaging cohort substudy of the National Survey of Health and Development (NSHD) study. Participants were prospectively recruited from the NSHD study, between May 18, 2020, and March 15, 2024, and underwent 3-Tesla contrast-enhanced CMR. An incidental finding was defined as a previously unknown abnormality that had not been identified by the participant or the research team before the study date. Incidental findings were classified into cardiac, non-cardiac, and clinical, and predefined according to the required urgency of follow-up as routine (reported to participants and their general practitioners within 28 days) or or immediate (reported within 48 hours). This study is registered with ClinicalTrials.gov, NCT05455125.

Findings: Of 505 participants prospectively recruited, 484 (96%) completed a full CMR scan. Of these, 432 (89%) had at least one incidental finding, including 58 (12%) immediate and 429 (89%) routine findings. Incidental findings were more common in male participants than in female participants (routine: 250 [92%] of 271 men vs 182 [85%] of 213 women, p=0·018; immediate: 39 [14%] of 271 men vs 19 [9%] of 213 women, p=0·069). The commonest routine cardiac incidental finding was late gadolinium enhancement (145 [43%] of 334 participants) and the commonest immediate cardiac finding was a left ventricular ejection fraction lower than 40% (seven [2%] of 334 participants). Non-cardiac incidental findings were predominantly routine (203 [42%] of 484) whereas immediate non-cardiac incidental findings were very uncommon (four [1%] of 484). Clinical findings were found in 201 (42%) of 484 participants, of which 28 (6%) were classified as immediate and 187 (39%) classified as routine.

Interpretation: CMR and baseline assessments revealed that incidental findings are common in imaging research in adults aged 75 years and older, underscoring the need for robust duty-of-care frameworks to ensure timely, ethical, and appropriate management of these findings in older age. These findings provide a population benchmark that can inform the design, governance, and resource planning of future large-scale imaging studies in ageing cohorts.

Funding: British Heart Foundation and Medical Research Council.

Background: Exercise can improve quality of life in women undergoing chemotherapy for breast cancer, but evidence of the most effective intervention characteristics remains inconclusive. The aim of this study was to determine the effect of exercise on quality of life in women with breast cancer during chemotherapy and examine whether its relationship varies by described exercise modality, dose, and other study characteristics.

Methods: In this systematic review and meta-analysis, a systematic search of five electronic databases (PubMed, Embase, Web of Science, Cochrane Library, and MEDLINE) from Jan 1, 2005, to May 24, 2025, identified randomised controlled trials evaluating exercise interventions and constructs of quality of life in women undergoing chemotherapy for breast cancer. Standardised mean differences (Hedges' g) were calculated and pooled using three-level random-effects models accounting for dependent effect sizes, and potential moderators were examined.

Findings: 21 randomised controlled trials (3024 participants) were included. Overall, exercise interventions showed a significant positive effect on constructs of quality of life (ḡ=0·434 [95% CI 0·272-0·595], p<0·0001). Substantial heterogeneity was observed (I²=55·76%). Described exercise modality significantly moderated effects (test statistic 3 for moderator differences 28·85, p<0·0001), with aerobic exercise (ḡ=0·482 [95% CI 0·272-0·595], p<0·0001), combined aerobic-strength training (ḡ=0·397 [0·156-0·639], p=0·0001), and strength-alone (ḡ=0·335 [0·002-0·669], p<0·049) showing significant benefits. This study is retrospectively registered with PROSPERO (CRD420251044479).

Interpretation: Exercise interventions significantly affect quality of life in women with breast cancer during chemotherapy. Aerobic and combined aerobic-strength training both showed significant benefits. Further research is needed to establish optimal exercise prescriptions.

Funding: None.

Current approaches to the role of artificial intelligence (AI) in the provision of long-term care for older people are largely framed around solving perceived problems in the sector, such as managing workforce shortages by driving greater efficiency through the automation of administrative and care tasks. Although such approaches might highlight some benefits of AI, they tend to overlook broader contextual and ethical implications within the complex structures of care systems. Thus, such narrow approaches can compromise care quality and pose risks for care recipients, caregivers, and care services. In this Personal View, we advocate for an alternative, care-centric approach to AI in long-term care, grounded in co-production and rooted in the view that care is a human need tied to wellbeing, dignity, equality, and human rights. We propose a definition of the responsible use of AI in long-term care with values of care at the forefront. We propose to use this definition as a starting point to drive AI policy and practice, rather than focusing on perceived problems, while also acknowledging and addressing tensions identified during the recent co-creation of responsible AI guidelines for the UK.