METHODOLOGY: A cross-sectional survey was conducted at two outpatient chemotherapy centers. A total of 546 patients completed the questionnaires on CAM use. QOL was evaluated based on the European Organization for Research and Treatment of Cancer (EORTC) core quality of life (QLQ-C30) and breast cancer-specific quality of life (QLQ-BR23) questionnaires.
RESULTS: A total of 70.7% of patients were identified as CAM users. There was no significant difference in global health status scores and in all five subscales of the QLQ C30 functional scales between CAM users and non-CAM users. On the QLQ-C30 symptom scales, CAM users (44.96±3.89) had significantly (p = 0.01) higher mean scores for financial difficulties than non-CAM users (36.29±4.81). On the QLQ-BR23 functional scales, CAM users reported significantly higher mean scores for sexual enjoyment (6.01±12.84 vs. 4.64±12.76, p = 0.04) than non-CAM users. On the QLQ-BR23 symptom scales, CAM users reported higher systemic therapy side effects (41.34±2.01 vs. 37.22±2.48, p = 0.04) and breast symptoms (15.76±2.13 vs. 11.08±2.62, p = 0.02) than non-CAM users. Multivariate logistic regression analysis indicated that the use of CAM modality was not significantly associated with higher global health status scores (p = 0.71).
CONCLUSION: While the findings indicated that there was no significant difference between users and non-users of CAM in terms of QOL, CAM may be used by health professionals as a surrogate to monitor patients with higher systemic therapy side effects and breast symptoms. Furthermore, given that CAM users reported higher financial burdens (which may have contributed to increased distress), patients should be encouraged to discuss the potential benefits and/or disadvantages of using CAM with their healthcare providers.
METHODOLOGY: Jaw sections containing 67 teeth (86 roots) were collected from unclaimed bodies due for cremation. Imaging was carried out to detect AP by digital PR with a central view (DP group), digital PR combining central with 10˚ mesially and distally angled (parallax) views (DPS group) and CBCT scans. All specimens underwent histopathological examination to confirm the diagnosis of AP. Sensitivity, specificity and predictive values of PR and CBCT were analysed using rater mean (n = 5). Receiver-operating characteristic (ROC) analysis was carried out.
RESULTS: Sensitivity was 0.27, 0.38 and 0.89 for DP, DPS and CBCT scans, respectively. CBCT had specificity and positive predictive value of 1.0 whilst DP and DPS had specificity and positive predictive value of 0.99. The negative predictive value was 0.39, 0.44 and 0.81 for DP, DPS and CBCT scans, respectively. Area under the curve (AUC) for the various imaging methods was 0.629 (DP), 0.688 (DPS), and 0.943 (CBCT).
CONCLUSIONS: All imaging techniques had similar specificity and positive predictive values. Additional parallax views increased the diagnostic accuracy of PR. CBCT had significantly higher diagnostic accuracy in detecting AP compared to PR, using human histopathological findings as a reference standard.
PATIENTS AND METHODS: CGA data was collected from 249 Asian patients aged 70 years or older. Nutritional risk was assessed based on the Nutrition Screening Initiative (NSI) checklist. Univariate and multivariate logistic regression analyses were applied to assess the association between patient clinical factors together with domains within the CGA and moderate to high nutritional risk. Goodness of fit was assessed using Hosmer-Lemeshow test. Discrimination ability was assessed based on the area under the receiver operating characteristics curve (AUC). Internal validation was performed using simulated datasets via bootstrapping.
RESULTS: Among the 249 patients, 184 (74%) had moderate to high nutritional risk. Multivariate logistic regression analysis identified stage 3-4 disease (Odds Ratio [OR] 2.54; 95% CI, 1.14-5.69), ECOG performance status of 2-4 (OR 3.04; 95% CI, 1.57-5.88), presence of depression (OR 5.99; 95% CI, 1.99-18.02) and haemoglobin levels <12 g/dL (OR 3.00; 95% CI 1.54-5.84) as significant independent factors associated with moderate to high nutritional risk. The model achieved good calibration (Hosmer-Lemeshow test's p = 0.17) and discrimination (AUC = 0.80). It retained good calibration and discrimination (bias-corrected AUC = 0.79) under internal validation.
CONCLUSION: Having advanced stage of cancer, poor performance status, depression and anaemia were found to be predictors of moderate to high nutritional risk. Early identification of patients with these risk factors will allow for nutritional interventions that may improve treatment tolerance, quality of life and survival outcomes.