Breast cancer is the most common malignancy in Jordan. Rigorous needs assessment for breast cancer patients can prioritize both cancer care and palliative care to propose the appropriate services effectively. We conducted a cross-sectional study of breast cancer patients in a cancer center in Jordan. We assessed symptom burden, comorbidities, and performance using the Edmonton Symptom Assessment System (ESAS), the Charlson Comorbidity Index (CCI), and the Australia-modified Karnofsky performance scale (AKPS). Descriptive analysis and regression models to predict the highest symptom burden were used. A total of 233 participants were enrolled: curative vs. palliative intent groups (147 (63%) vs. 86 (37%) patients), respectively. Tiredness was the most reported symptom in 189 patients (81%), while nausea was the least in 61 patients (26.2%). A relationship between the AKPS score and total ESAS was seen (correlation coefficient of −0.487; p < 0.0001). The prevalence of anxiety (p = 0.014), lack of appetite (p = 0.002), poor well-being (p < 0.001), and sleep disorder (p = 0.035) was higher in the palliative care intent group than in the curative one. We identified unmet needs in breast cancer patients. Both groups showed a prevalence of distressing symptoms suggesting that even those with non-palliative intent have high needs and should receive integrated palliative care.

Purpose: The study explores a clinical model based on aging-care parameters to predict the mortality of hospitalized patients aged 80-year and above with community-acquired pneumonia (CAP). Patients and methods: In this study, four hundred and thirty-five CAP patients aged 80-years and above were enrolled in the Central Hospital of Minhang District, Shanghai during 01,01,2018– 31,12,2021. The clinical data were collected, including aging-care relevant factors (ALB, FRAIL, Barthel Index and age-adjusted Charlson Comorbidity Index) and other commonly used factors. The prognostic factors were screened by multivariable logistic regression analysis. Receiver operating characteristic (ROC) curves were used to predict the mortality risk. Results: Univariate analysis demonstrated that several factors, including gender, platelet distribution width, NLR, ALB, CRP, pct, pre-albumin, CURB-65, low-density, lipoprotein, Barthel Index, FRAIL, leucocyte count, neutrophil count, lymphocyte count and aCCI, were associated with the prognosis of CAP. Multivariate model analyses further identified that CURB-65 (p < 0.0001, OR = 5.44, 95% CI = 3.021– 10.700), FRAIL (p < 0.0001, OR = 5.441, 95% CI = 2.611– 12.25) and aCCI (p = 0.003, OR = 1.551, 95% CI = 1.165– 2.099) were independent risk factors, whereas ALB (p = 0.005, OR = 0.871, 95% CI = 0.788– 0.957) and Barthel Index (p = 0.0007, OR = 0.958, 95% CI = 0.933– 0.981) were independent protective factors. ROC curves were plotted to further predict the in-hospital mortality and revealed that combination of three parameters (Barthel Index+ FRAI +CURB-65) showed the best performance. Conclusion: This study showed that CURB-65, frailty and aCCI were independent risk factors influencing prognosis. In addition, ALB and Barthel Index were protective factors for in CAP patients over 80-years old. AUC was calculated and revealed that combination of three parameters (Barthel Index+ FRAI +CURB-65) showed the best performance.