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In cancer cachexia trials, measures of physical function are commonly used as endpoints. For drug trials to obtain regulatory approval, efficacy in physical function endpoints may be needed alongside other measures. However, it is not clear which physical function endpoints should be used. The aim of this systematic review was to assess the frequency and diversity of physical function endpoints in cancer cachexia trials. Following a comprehensive electronic literature search of MEDLINE, Embase and Cochrane (1990-2021), records were retrieved. Eligible trials met the following criteria: adults (≥18 years), controlled design, more than 40 participants, use of a cachexia intervention for more than 14 days and use of a physical function endpoint. Physical function measures were classified as an objective measure (hand grip strength [HGS], stair climb power [SCP], timed up and go [TUG] test, 6-min walking test [6MWT] and short physical performance battery [SPPB]), clinician assessment of function (Karnofsky Performance Status [KPS] or Eastern Cooperative Oncology Group-Performance Status [ECOG-PS]) or patient-reported outcomes (physical function subscale of the European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaires [EORTC QLQ-C30 or C15]). Data extraction was performed using Covidence and followed PRISMA guidance (PROSPERO registration: CRD42022276710). A total of 5975 potential studies were examined and 71 were eligible. Pharmacological interventions were assessed in 38 trials (54%). Of these, 11 (29%, n = 1184) examined megestrol and 5 (13%, n = 1928) examined anamorelin; nutritional interventions were assessed in 21 trials (30%); and exercise-based interventions were assessed in 6 trials (8%). The remaining six trials (8%) assessed multimodal interventions. Among the objective measures of physical function (assessed as primary or secondary endpoints), HGS was most commonly examined (33 trials, n = 5081) and demonstrated a statist

Nausea and vomiting are often associated with opioid analgesia in cancer patients; however, only a subset of patients develop such side effects. Here, we tested the hypothesis that the occurrence of nausea and vomiting is modulated by the genetic background of the patients. Whole exome sequencing of DNA pools from patients with either low (n = 937) or high (n = 557) nausea and vomiting intensity, recruited in the European Pharmacogenetic Opioid Study, revealed a preliminary association of 53 polymorphisms. PCR-based genotyping of 45 of these polymorphisms in the individual patients of the same series confirmed the association for six SNPs in AIM1L, CLCC1, MUC16, PDE3A, POM121L2, and ZNF165 genes. Genotyping of the same 45 polymorphisms in 264 patients of the Italian CERP study, also treated with opioids for cancer pain, instead confirmed the association for two SNPs in ZNF568 and PDE3A genes. Only one SNP, rs12305038 in PDE3A, was confirmed in both series, although with opposite effects of the minor allele on the investigated phenotype. Overall, our findings suggest that genetic factors are indeed associated with nausea and vomiting in opioid-treated cancer patients, but the role of individual polymorphisms may be weak.

The International Classification of Diseases-11 (ICD-11) chronic pain classification includes about 100 chronic pain diagnoses on different diagnostic levels. Each of these diagnoses requires specific operationalized diagnostic criteria to be present. The classification comprises more than 200 diagnostic criteria. The aim of the Classification Algorithm for Chronic Pain in 1CD-11 (CAL-CP) is to facilitate the use of the classification by guiding users through these diagnostic criteria. The diagnostic criteria were ordered hierarchically and visualized in accordance with the standards defined by the Society for Medical Decision Making Committee on Standardization of Clinical Algorithms. The resulting linear decision tree underwent several rounds of iterative checks and feedback by its developers, as well as other pain experts. A preliminary pilot evaluation was conducted in the context of an ecological implementation field study of the classification itself. The resulting algorithm consists of a linear decision tree, an introduction form, and an appendix. The initial decision trunk can be used as a standalone algorithm in primary care. Each diagnostic criterion is represented in a decision box. The user needs to decide for each criterion whether it is present or not, and then follow the respective yes or no arrows to arrive at the corresponding ICD-11 diagnosis. The results of the pilot evaluation showed good clinical utility of the algorithm. The CAL-CP can contribute to reliable diagnoses by structuring a way through the classification and by increasing adherence to the criteria. Future studies need to evaluate its utility further and analyze its impact on the accuracy of the assigned diagnoses.

Introduction: Poorer end-of-life (EOL) care for elderly cancer patients has been reported. We assessed the impact of age on 13 indicators for the quality of EOL care as well as adherence to 6 national quality indicators in gynaecological cancer patients. Methods: Age-dependent differences in 13 palliative care quality indicators were studied in gynaecological cancer patients registered in the population-based Swedish Register of Palliative Care. Association between the patient's age and each quality indicator was analyzed by logistic regression, adjusted for place of death where appropriate. Adherence to six national quality indicators determined by the Swedish National Board of Health and Welfare was estimated in all patients. Results: We included 3940 patients with the following age distribution: 1.6% were 18-39 years of age, 12.3% 40-59 years, 37.2% 60-74 years, 28.9% 75-84 years and 20% were ≥85 years. Age-dependent differences in implementation rate were present for some of the 13 quality indicators. Compared to elderly cancer patients, younger patients were more likely to be cared for by a specialized palliative care service, more often informed about imminent death as well as assessed for pain. For most national quality indicators, the goal level was not met. Only for the 'on demand prescription for pain', the goal level was reached. Conclusions: EOL care did not meet national quality indicators in this population-based data from Sweden, in particular in the elderly population. Elderly gynaecological cancer patients are at high risk of poorer EOL care without the involvement of specialized palliative care services. Palliative care services need to be implemented across all institutions of EOL care to ensure good and equal care.

CONTEXT:Patients with advanced cancer commonly suffer from both distressing symptoms and cognitive impairment, but the effect of cognitive impairment on the reliability and validity of symptom self-report is unknown. OBJECTIVES:To evaluate the reliability and validity of symptom self-report in cancer outpatients with and without mild to moderate cognitive impairment. METHODS:This was an analysis of the longitudinal European Palliative Care Cancer Symptom study of adults with incurable cancer in specialized palliative care (30 centers across 12 countries). Patients who could not comply with the study because of severe cognitive impairment were excluded. Cognitive status on the Mini-Mental State Examination short version and nine symptoms (pain, tiredness, drowsiness, nausea, appetite, breathlessness, depression, anxiety, and well-being) using the revised Edmonton Symptom Assessment System were self-reported at baseline and one-month follow-up. Reliability was analyzed using intraclass correlation coefficients and validity using regression of each symptom with health-related quality of life (HrQoL) measured with European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 15 for Palliative Care. RESULTS:A total of 1047 patients were included: mean age of 62.9 years; 54.4% women; main cancer types were of digestive organs (26.6%), breast (21.6%), and lungs (21.2%). Cognitive impairment was present in 181 (17.3%) at baseline and associated with worse self-reported tiredness, drowsiness, appetite, and depression. Reliability (intraclass correlation coefficient) and validity (associations with HrQoL) were similar between people with/without cognitive impairment across the nine symptoms, except breathlessness, which showed a weaker relation to HrQoL in patients with cognitive impairment. Findings were robust in sensitivity analyses and after controlling for potential confounders. CONCLUSION:In advanced cancer, self-report of nine major symp

© 2019 American Academy of Hospice and Palliative Medicine Context: Minimizing bias in randomized controlled trials (RCTs) includes intention-to-treat analyses. Hospice/palliative care RCTs are constrained by high attrition unpredictable when consenting, including withdrawals between randomization and first exposure to the intervention. Such withdrawals may systematically bias findings away from the new intervention being evaluated if they are considered nonresponders. Objectives: This study aimed to quantify the impact within intention-to-treat principles. Methods: A theoretical model was developed to assess the impact of withdrawals between randomization and first exposure on study power and effect sizes. Ten reported hospice/palliative care studies had power recalculated accounting for such withdrawal. Results: In the theoretical model, when 5% of withdrawals occurred between randomization and first exposure to the intervention, change in power was demonstrated in binary outcomes (2.0%–2.2%), continuous outcomes (0.8%–2.0%), and time-to-event outcomes (1.6%–2.0%), and odds ratios were changed by 0.06–0.17. Greater power loss was observed with larger effect sizes. Withdrawal rates were 0.9%–10% in the 10 reported RCTs, corresponding to power losses of 0.1%–2.2%. For studies with binary outcomes, withdrawal rates were 0.3%–1.2% changing odds ratios by 0.01–0.22. Conclusion: If blinding is maintained and all interventions are available simultaneously, our model suggests that excluding data from withdrawals between randomization and first exposure to the intervention minimizes one bias. This is the safety population as defined by the International Committee on Harmonization. When planning for future trials, minimizing the time between randomization and first exposure to the intervention will minimize the problem. Power should be calculated on people who receive the intervention.