Sarcopenia is a multifactorial age-related muscle disorder of which its underlying pathophysiological mechanisms remain incompletely understood. To date, treatment strategies of sarcopenia have been largely confined to lifestyle interventions, underscoring an urgent need for pharmacological options that directly target the biological drivers of muscle deterioration. Despite increasing interest in drug development for sarcopenia, no specific pharmacological agent has yet received regulatory approval. This review provides a comprehensive synthesis of recent advances in investigational pharmacotherapeutic options for sarcopenia, with a focus on their mechanistic pathways and evidence from clinical trials. Key emerging classes include selective androgen receptor modulators (SARMs), myostatin antibodies, monoclonal antibodies targeting activin type 2 receptors, ghrelin receptor agonists, and growth differentiation factor-15 (GDF-15) monoclonal antibodies. In parallel, existing medications including testosterone, antidiabetic agents, classical renin-angiotensin system (RAS) inhibitors and anti-inflammatory drugs, have shown ancillary benefits in older populations but lack robust, indication-specific data. A critical contradiction persists: while several candidates increase muscle mass, few consistently improve muscle strength or physical function, reflecting a disconnect between surrogate endpoints and clinically meaningful outcomes. Moreover, some trials have been conducted in heterogeneous populations without clearly defined sarcopenia, limiting interpretability. As mechanistic insights evolve and regulatory frameworks advance, the field requires not only more targeted therapies but also clearer definitions of efficacy and patient classification.

Introduction Chronic obstructive pulmonary disease (COPD) has an unpredictable clinical course, causing difficulties in short-term mortality prediction, overtreatment and delayed palliative care. Existing prediction models are limited and lack applicability to Chinese elderly patients with advanced COPD. Given the heavy disease burden and limited palliative care in China, we designed this multicentre cohort study to develop a 6-month mortality prediction model for elderly patients with advanced COPD to aid risk stratification, timely palliative care and efficient healthcare resource allocation. Methods and analysis Patient recruitment has been ongoing since May 2024 and will be completed by December 2026, with a 12-month follow-up to be completed by December 2027. Eligible patients are being enrolled, and multidimensional baseline data including demographic characteristics, clinical indicators, laboratory results, comprehensive geriatric assessment and COPD-specific prognostic factors are being systematically collected. All participants will receive 12 months of standardised follow-up (monthly for the first 6 months and quarterly thereafter) to monitor 6-month all-cause mortality (primary outcome), as well as survival duration, end-of-life healthcare utilisation and do-not-resuscitate status (secondary outcomes). After completion of data collection, we will employ multiple machine learning algorithms to develop and internally validate a 6-month mortality prediction model with pre-specified centres reserved for external validation. Model performance will be evaluated by discrimination and calibration and head-to-head comparisons with the Body Mass Index, Airflow Obstruction, Dyspnoea and Exercise Capacity (BODE) and Age, Dyspnoea and Airflow Obstruction (ADO) indices will be conducted to verify its clinical value. The findings will provide a China-specific prediction tool for elderly patients with advanced COPD to guide clinical intervention, palliative care referral and healthcare resource allocation. Ethics and dissemination This study was approved by the Biomedical Ethics Review Committee of West China Hospital, Sichuan University (No. 2024-2662) and registered at ChiCTR2500100351. Informed consent is being obtained from all participants. Results will be published in peer-reviewed journals and presented at academic conferences.Trial registration number ChiCTR2500100351.

Introduction:Reliable sarcopenia risk prediction models are essential for identifying older adults who are currently non-sarcopenic but at risk of developing sarcopenia in the future, thereby enabling early and personalized prevention strategies. However, the prediction models for sarcopenia have not yet been systematically evaluated. This systematic review aimed to conduct a comprehensive overview and critical appraisal of current sarcopenia risk prediction models. Methods:We conducted a systematic search across MEDLINE, Embase, Cochrane Library, and SCI-EXPANDED. Eligible primary studies on sarcopenia prediction models were identified based on the CHARMS checklist (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies). The Prediction model Risk Of Bias Assessment Tool (PROBAST) was applied to evaluate risk of bias and clinical applicability. Results:Twenty-six sarcopenia prediction models were identified, mostly targeting community-dwelling older adults or patients. Twenty-three studies developed diagnostic prediction models, while only three studies established sarcopenia prognostic models. Age, BMI, calf circumference and gender were most frequently utilized predictors. Despite reported discriminative performance ranging from moderate to excellent (AUC > 0.70), 96.1% of prediction models exhibited high risk of bias due to significant methodological shortcomings, suggesting that model performance might be overestimated. Moreover, most existing prediction models were diagnostic study design, limiting their ability to predict the future risk of sarcopenia development. Conclusion:Most existing sarcopenia prediction models demonstrated moderate to high discriminatory performance. However, due to their predominantly diagnostic study design and high risk of bias, these models cannot yet be broadly recommended for routine clinical application in the early identification of high-risk older adults with sarcopenia. Future studies are needed to develop and externally validate practical, accurate prognostic sarcopenia models to fulfill sarcopenia early prevention. Systematic review registration:The protocol has been registered on the Open Science Framework (10.17605/OSF. IO/BFDK6).

We performed this systematic review and meta-analysis to explore the impact of preoperative sarcopenia on postoperative complication risks after head and neck cancer (HNC) surgery. We identified eligible studies by searching Ovid-MEDLINE, Ovid-Embase, EBM Reviews-Cochrane Central Register of Controlled Trials, Web of Science Core Collection, and Scopus. This systematic review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidance. Twenty-one studies with a total of 3480 patients met our inclusion criteria. The presence of sarcopenia significantly increased the incidence of overall postoperative complications (OR = 1.72, 95

Objectives: To assess the role of a pre-chemotherapy frailty index based on routine laboratory data in predicting mortality and chemotherapy adverse reactions among older patients with primary lung cancer. Design: Retrospective cohort study Setting: West China Hospital, Chengdu, China Participants: We included patients aged >= 60 years with primary lung cancer receiving the first course of chemotherapy. Measurements: Data were collected from medical records, local government death databases or telephone interviews. Outcomes included chemotherapy adverse reactions and all-cause mortality. We constructed a frailty index based on 44 laboratory variables (FI-LAB) before chemotherapy, and chose the following cutoff points: robust (0.0-0.2), pre-frail (0.2-0.35) and frail (>= 0.35). Results: We included 1,020 patients (71.4% male; median age: 65 years old). Both pre-frailty and frailty was associated with any chemotherapy adverse reactions and infections during chemotherapy (OR=3.48, 95%CI: 1.77-6.87; OR=3.58, 95%CI: 1.55-8.26, respectively). Frail patients had a shorter median overall survival rate compared to robust patients (18.05 months vs 38.89 months, log-rank p<0.001). After adjusting for some potential confounding variables, the risk of all-cause mortality was dramatically increased in frail patients (HR:2.13, 95% CI:1.51-3.00) with an average follow-up of 3.9 years. Each 0.01 or per standard deviation (SD) increase in the FI-LAB value significantly increased the HR of death by 2.0% (HR:1.02, 95% CI: 1.01-1.03) and 23.0% (HR: 1.23, 95% CI: 1.13-1.34), respectively. Conclusions: Frailty assessed by routine laboratory data indicates increased risks of chemotherapy adverse reactions and death in older patients with primary lung cancer receiving the first course of chemotherapy.