Background: More than half of patients with breast cancer were diagnosed with locally advanced stages of the disease (54%). This study aimed to explain the pathological response received with neoadjuvant chemotherapy (NACT) according to the molecular classi cation of breast cancer in patients with locally advanced tumors.Methods: One hundred one patients with locally advanced breast cancer treated with neoadjuvant chemotherapy were analyzed. Patients were classi ed into ve molecular subtypes based on the pro le of the estrogen receptor, progesterone receptor, HER2, and Ki-67. We determined associations between pathologic complete response and molecular subgroups.Results: Most patients had luminal A tumors (n:28, 27.7%). The overall rate of pathological complete response (pCR) was 34.7% (n:35). Tumors that presented the highest rate of pCR were pure HER2positive, at 60% (n:6; OR, 3.2; 95% CI, 0.8-12.2). According to logistic regression analysis, the factors affecting pCR were HER2 positivity and clinically positive axilla before NACT. Luminal A tumors had a signi cantly lower pCR rate. (7.1%,p: 0.001). Despite the low pCR rate, luminal A tumor survival was the best subgroup (p< 0.001). However, there was no difference between EFS and OS according to pCR in any molecular subgroups.Conclusion: Pathological complete response is directly related to the subtypes of breast cancer. A high rate of complete pathological response is observed in the pure HER2-positive group. However, EFS and OS were not statistically signi cant in patients with and without pCR.

This study aimed to assess whether dabrafenib/trametinib and vemurafenib/cobimetinib treatments are associated with a change in skeletal muscle area (SMA) and total fat-free mass (FFM) assessed by computed tomography (CT), and to compare the efficacy and safety profile of these treatments in patients with metastatic melanoma. Thirty-one patients treated with B-Raf proto-oncogene, serine/threonine kinase/MAPK extracellular receptor kinase inhibitors were included between 2016 and 2019. Eighteen patients received dabrafenib/trametinib and remaining patients received vemurafenib/cobimetinib. CT scans were performed at baseline and at 4–6 months of follow-up to measure cross-sectional areas of SMA. FFM and skeletal muscle index (SMI) values were calculated. Of the patients, including 18 treated with dabrafenib/trametinib (58.1%) and 13 with vemurafenib/cobimetinib (41.9%); 58.1% were male, 41.9% were female and median age was 52 years. A significant decrease in SMA was observed after dabrafenib/trametinib and vemurafenib/cobimetinib treatments (P = 0.003 and P = 0.002, respectively). A significant decrease in FFM values was observed after dabrafenib/trametinib and vemurafenib/cobimetinib treatments (P = 0.003 and P = 0.002, respectively). Dose-limiting toxicity (DLT) was observed in 35.9% of the patients with sarcopenia. No significant difference was seen between the dabrafenib/trametinib and vemurafenib/cobimetinib groups in median progression-free survival (PFS) (11.9 vs. 7.3 months, respectively, P = 0.28) and in median overall survival (OS) (25.46 vs. 13.7 months, respectively, P = 0.41). Baseline sarcopenia was not significantly associated with PFS or OS (P = 0.172 and P = 0.326, respectively). We found a significant decrease in SMI values determined at 4–6 months compared to the values before treatment both in dabrafenib/trametinib and vemurafenib/cobimetinib groups. DLT was similar with both treatments. Baseline sarcopenia was not significantly associated with PFS or OS.

Undoubtedly, cancer patients have suffered the most from the COVID‐19 pandemic process. However, cancer is a heterogeneous disease, and each patient has responded differently to COVID‐19. We aimed to describe the clinical characteristics and outcomes of patients with cancer and COVID‐19. We retrospectively reviewed 45 cancer patients hospitalized in the Cerrahpaşa Medical Faculty COVID‐19 department from March 23 to October 23, 2020. We analyzed the demographic characteristics, symptoms, laboratory findings, treatment, prognosis, and cancer subtypes of patients and mortality who were hospitalized for COVID‐19. Between March 23 and October 23, 2020, 45 hospitalized cancer patients who had laboratory‐confirmed COVID‐19 infection were included, with a median age of 60 years (range: 23–92). Patients were divided into two groups a survivor and a non‐survivor. Symptoms, demographic information, comorbidities, treatments for COVID‐19, and laboratory findings of the two groups were evaluated separately. Two parameters were found, which showed a significant difference between non‐survivors and survivors displaying a disadvantage for COPD and low platelet count ( p = 0.044–0.038). The mortality rate of all patients was 66%. The presence of comorbidities such as COPD and low platelet count in cancer patients with COVID‐19 infection may draw the attention of physicians.

Introduction: With the widespread use of immune checkpoint inhibitors (ICIs), we are facing challenges in the management of immune-related adverse events (irAEs). We aimed to characterize the spectrum of toxicity, management, and outcomes for irAEs. Methods: Patients who were treated with at least one ICI in clinical trials, expanded access programs, or routine clinical practice were included. Clinical and laboratory parameters were collected retrospectively to determine the incidence of irAEs, methods of management, and treatment outcomes. Results: A total of 255 patients were screened retrospectively. Of these, 71 (27.8%) patients developed irAEs. More than 2 different types of irAEs were detected in 16 (6.2%) out of 255 patients. A total of 3177 doses were given to 255 patients. In 93 (2.9%) of the 3177 doses, 1 episode of irAEs was experienced. A total of 22 out of 93 (23.7%) episodes were reported as grade 1, 49 (52.7%) as grade 2, 19 (20.4%) as grade 3, and 3 (3.2%) as grade 4. The most frequently seen irAEs were pneumonitis, hepatitis, and hypothyroidism. With regard to treatment, 39 out of 93 episodes (42%) of any grade irAEs occurred after anti–programmed cell death-1 therapy, 47 (50.5%) occurred following administration of anti–programmed death-ligand 1, and 7 (7.5%) occurred after combination treatments. Conclusion: With the increased use of immunotherapeutic agents, increased awareness and early recognition are required for effective management of irAEs. Our experience as a single institution might be of use for health care providers in oncology.

Background: Most of the studies on salivary gland cancers are limited for various reasons such as being single-center, small number of patients, including only major or minor SGCs, or only including epidemiological data.Methods: A total of 37 medical oncology clinics from different regions of Turkey participated in this retrospective-multicenter study. The analyzed data included clinical and demographical features, primary treatment, metastasis localizations, and treatments and includes certain pathologic features.

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Sleep disorders are one of the most common problems in patients with malignancy and they severely decrease the quality of life. We sought to investigate the frequency of sleep disturbances, its quantity, quality and possible correlation with related factors such as depression and anxiety. Materials and Methods: 150 patients participated and the Pittsburgh Sleep Quality Index was used to evaluate the sleep quality. It is a self-administered questionnaire and standardized measure of sleep quality. Total score of ≥5 shows that the quality of sleep is remarkably bad. Also a self-report measure of depression, the Beck Depression Inventory (BDI); and a self-report measure of anxiety, Beck Anxiety Inventory (BAI) were used. Results: Of the 150 patients, 74.0% has bad sleep quality (score >5). Mean PSQI total score was 7.34 (min 0-max 20). No differences were found between PSQI mean scores in terms of gender, radiotherapy (RT), chemotherapy (CHT), having chronic disease or having metastatic disease. NSAIDs and opioids were significantly correlated with PSQI (p<0.001). PSQI total scores are strongly associated with the BDI score (r=.424, p<0.001) and BAI score (r=.417, p<0.001). Conclusion: We found a high prevalence rate of bad sleep quality at 74%. Effective sleep treatment and psychological support should be provided in oncology clinics.