The Possible Role of Anti- and Protumor-Infiltrating Lymphocytes in Pathologic Complete Response in Early Breast Cancer Patients Treated with Neoadjuvant Systemic Therapy.

The tumor microenvironment, composed of pro- and antitumor immune cells, affects cancer cell behavior. We aimed to evaluate whether tumor-infiltrating lymphocyte (TIL) density and TIL subtypes in core biopsies at the diagnosis of breast cancer patients could predict a pathologic complete response (pCR; ypT0/is ypN0) from neoadjuvant systemic therapy (NST). The TIL subtypes were determined based on the proportions of presumably antitumor (CD8+, CXCL13+) and protumor (PD-1+, FOXP3+) immune cells. A prospective, noninterventional study, including 171 participants undergoing NST, was performed. The median TIL density for the entire cohort was 10% (IQR: 3.5-23.8), and 59 (35%) patients achieved pCR. TIL density was positively associated with pCR (univariately and multivariably). In the multivariable logistic regression model, TIL density was an independent predictor of pCR (p = 0.012, OR 1.27; 95% CI 1.05-1.54) when controlled for age (p = 0.232), Ki-67 (p = 0.001), node-negative status (p = 0.024), and HER2+/triple negative vs. luminal B-like subtype (p < 0.001). In our sample, higher proportions of PD-1+ TILs and FOXP3+ TILs were associated with a higher probability of pCR but the association was not statistically significant and we could not make any conclusions on the direction of associations in the model with all four biomarkers. In the exploratory multivariable analysis, we showed that only higher CD8+ TILs were associated with pCR. In conclusion, TIL density and its subtypes are associated with pCR.

Treatment outcomes and relative dose intensity of chemotherapy in patients with advanced Hodgkin lymphoma.

The present retrospective study was undertaken to investigate the association of relative dose intensity (RDI) with the outcome of patients with advanced stage Hodgkin lymphoma (HL) receiving ABVD (doxorubicin, bleomycin, vinblastine, dacarbazine) and escalated BEACOPP regimens (bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, prednisone). A total of 114 patients with HL treated between 2004 and 2013 were enrolled for evaluation. The association of variables with overall survival (OS) and progression-free survival (PFS) was analysed using univariate and multivariate Cox proportional hazards models. The median age of patients was 39 years, and the majority were male and had stage IV disease. A total of 54 patients received ABVD and 60 received BEACOPP chemotherapy with 24 and four deaths, respectively. Patients in the BEACOPP group were significantly younger with lower Charlson comorbidity index (CCI) and better performance status in comparison with the ABVD group, making the comparison of groups not possible. In the ABVD group, RDI was not significantly associated with OS (P=0.590) or PFS (P=0.354) in a multivariate model where age was controlled. The low number of events prevented this analysis in the BEACOPP group. The age of patients was strongly associated with both OS and PFS; all statistically significant predictors for OS and PFS from univariate analyses (chemotherapy regimen, CCI, RDI, performance status) lost their effect in multivariate analyses where age was controlled. Based on these observations, it was concluded that RDI was not associated with OS or PFS after age is controlled, neither in all patients combined nor in the ABVD group.

Mobile App for Symptom Management and Associated Quality of Life During Systemic Treatment in Early Stage Breast Cancer: Nonrandomized Controlled Prospective Cohort Study.

BACKGROUND: Providing patients with cancer who are undergoing systemic therapy with useful information about symptom management is essential to prevent unnecessary deterioration of quality of life. OBJECTIVE: The aim was to evaluate whether use of an app for symptom management was associated with any change in patient quality of life or use of health resources. METHODS: Outpatients with early stage breast cancer receiving systemic therapy were recruited at the Institute of Oncology in Ljubljana, Slovenia. Patients who received systemic therapy between December 2017 and March 2018 (control group) and between April 2018 and September 2018 (intervention group) were eligible. All patients received standard care, but only those in the intervention group were asked to use mPRO Mamma, an Android-based smartphone app, in addition. The app supported daily tracking of 50 symptoms, allowed users to grade their symptom severity (as mild, moderate, or severe), and also provided in-depth descriptions and recommendations based on reported symptom level. Patient-reported outcomes in both groups were assessed through the European Organisation for Research and Treatment of Cancer (EORTC) core (C-30) and breast cancer (BR-23) questionnaires, as well as a questionnaire about health resources use. The primary outcomes were the difference in the global quality of life between groups and the difference in summary score of the EORTC C-30 questionnaire between groups after 3 time periods (the first week of treatment, the first treatment cycle, and the entire treatment). The secondary outcome was the use of health resources (doctor visits and hospitalizations) in each time period. Other scales were used for exploratory analysis. RESULTS: The mean difference between the intervention group (n=46) and the control group (n=45) in global quality of life (adjusted for baseline and type of surgery) after the first week was 10.1 (95% CI 1.8 to 18.5, P=.02). The intervention group summary scores were significantly higher than those of the control group after the first week (adjusted mean difference: 8.9, 95% CI 3.1 to 14.7, P=.003) and at the end of treatment (adjusted mean difference: 10.6, 95% CI 3.9 to 17.3, P=.002). Use of health resources was not statistically significant between the groups in either the first week (P=.12) or the first treatment cycle (P=.13). Exploratory analysis findings demonstrated clinically important improvements (indicated by EORTC C-30 or BR-23 scale scores)-social, physical, role, and cognitive function were improved while pain, appetite loss, and systemic therapy side effects were reduced. CONCLUSIONS: Use of the app enabled patients undergoing systemic therapy for early stage breast cancer to better cope with symptoms which was demonstrated by a better global quality of life and summary score after the first week and by a better summary score at the end of treatment in the intervention group compared to those of the control group, but no change in the use of health resources was demonstrated.

Risk for malnutrition in family practice non-attenders living in the community: A cross-sectional study from Slovenia.

OBJECTIVES: The aim of this study was to determine the prevalence of malnutrition and the factors associated with malnutrition in a population of family practice non-attenders. This would enable us to recognize the extent of the problem and anticipate the measures needed to improve the current situation. METHODS: This was a cross-sectional observational study in a family medicine setting. Participants were adults living in the community (≥18 y of age) who had not visited their chosen family physician in the previous 5 y (non-attenders) and who were able to participate in the study. Through the electronic system, we identified 2025 non-attenders. Data were collected by community nurses in the participants' homes. The main outcome measure was the Malnutrition Universal Screening Tool. RESULTS: The sample consisted of 1641 participants (81% response rate). Increased risk for malnutrition was determined in 216 participants (13.2%; 95% confidence interval, 11.6-14.9). The multivariate model showed a significant association of increased risk for malnutrition with age and body mass index interaction (P = 0.022); number of chronic diseases (P = 0.001); poor assessment of current health (P = 0.001); a feelings of loneliness (P <0.001); and increased pain intensity (P = 0.003). CONCLUSION: A screening program at the primary health care level could help identify patients at risk for malnutrition early. This could be followed by appropriate nutrition support, which may help to reverse or halt the malnutrition trajectory and the negative outcomes associated with poor nutritional status.