Background: In the phase III IMpassion130 trial, combining atezolizumab with first-line nanoparticle albumin-boundpaclitaxel for advanced triple-negative breast cancer (aTNBC) showed a statistically significant progression-free survival (PFS) benefit in the intention-to-treat (ITT) and programmed death-ligand 1 (PD-L1)-positive populations, and a clinically meaningful overall survival (OS) effect in PD-L1-positive aTNBC. The phase III KEYNOTE-355 trial adding pembrolizumab to chemotherapy for aTNBC showed similar PFS effects. IMpassion131 evaluated first-line atezolizumabepaclitaxel in aTNBC. Patients and methods: Eligible patients [no prior systemic therapy or 12 months since (neo)adjuvant chemotherapy] were randomised 2:1 to atezolizumab 840 mg or placebo (days 1, 15), both with paclitaxel 90 mg/m 2 (days 1, 8, 15), every 28 days until disease progression or unacceptable toxicity. Stratification factors were tumour PD-L1 status, prior taxane, liver metastases and geographical region. The primary endpoint was investigator-assessed PFS, tested hierarchically first in the PD-L1-positive [immune cell expression 1%, VENTANA PD-L1 (SP142) assay] population, and then in the ITT population. OS was a secondary endpoint. Results: Of 651 randomised patients, 45% had PD-L1-positive aTNBC. At the primary PFS analysis, adding atezolizumab to paclitaxel did not improve investigator-assessed PFS in the PD-L1-positive population [hazard ratio (HR) 0.82, 95% confidence interval (CI) 0.60-1.12; P ¼ 0.20; median PFS 6.0 months with atezolizumabepaclitaxel versus 5.7 months with placeboepaclitaxel]. In the PD-L1-positive population, atezolizumabepaclitaxel was associated with more favourable unconfirmed best overall response rate (63% versus 55% with placeboepaclitaxel) and median duration of response (7.2 versus 5.5 months, respectively). Final OS results showed no difference between arms (HR 1.11, 95% CI 0.76-1.64; median 22.1 months with atezolizumabepaclitaxel versus 28.3 months with placeboe paclitaxel in the PD-L1-positive population). Results in the ITT population were consistent with the PD-L1-positive population. The safety profile was consistent with known effects of each study drug. Conclusion: Combining atezolizumab with paclitaxel did not improve PFS or OS versus paclitaxel alone. ClinicalTrials.gov: NCT03125902.

Blood-based biomarkers reflect systemic inflammation status and have prognostic and predictive value in solid malignancies. As a recently defined biomarker, Pan-Immune-Inflammation-Value (PIV) integrates different peripheral blood cell subpopulations. This retrospective study of collected data aimed to assess whether PIV may predict the pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in Turkish women with breast cancer. The study consisted of 743 patients with breast cancer who were scheduled to undergo NAC before attempting cytoreductive surgery. A pre-treatment complete blood count was obtained in the two weeks preceding NAC, and blood-based biomarkers were calculated from absolute counts of relevant cell populations. The pCR was defined as the absence of tumor cells in both the mastectomy specimen and lymph nodes. Secondary outcome measures included disease-free survival (DFS) and overall survival (OS). One hundred seven patients (14.4%) had pCR. In receiver operating characteristic analysis, optimal cut-off values for the neutrophile-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte (PLR), PIV, and Ki-67 index were determined as ≥ 2.34, ≥ 0.22, ≥ 131.8, ≥ 306.4, and  ≥ 27, respectively. The clinical tumor (T) stage, NLR, MLR, PLR, PIV, estrogen receptor (ER) status, human epidermal growth factor receptor-2 (HER-2) status, and Ki-67 index were significantly associated with NAC response in univariate analyses. However, multivariate analysis revealed that the clinical T stage, PIV, ER status, HER-2 status, and Ki-67 index were independent predictors for pCR. Moreover, the low PIV group patients had significantly better DFS and OS than those in the high PIV group (p = 0.034, p = 0.028, respectively). Based on our results, pre-treatment PIV seems as a predictor for pCR and survival, outperforming NLR, MLR, PLR in predicting pCR in Turkish women with breast cancer who received NAC. However, further studies are needed to confirm our findings.

Background: Medication errors in oncology may cause severe clinical problems due to low therapeutic indices and high toxicity of chemotherapeutic agents. We aimed to investigate unintentional medication errors and underlying factors during chemotherapy preparation and administration based on a systematic survey conducted to reflect oncology nurses experience. Materials and Methods: This study was conducted in 18 adult chemotherapy units with volunteer participation of 206 nurses. A survey developed by primary investigators and medication errors (MAEs) defined preventable errors during prescription of medication, ordering, preparation or administration. The survey consisted of 4 parts: demographic features of nurses; workload of chemotherapy units; errors and their estimated monthly number during chemotherapy preparation and administration; and evaluation of the possible factors responsible from ME. The survey was conducted by face to face interview and data analyses were performed with descriptive statistics. Chi-square or Fisher exact tests were used for a comparative analysis of categorical data. Results: Some 83.4% of the 210 nurses reported one or more than one error during chemotherapy preparation and administration. Prescribing or ordering wrong doses by physicians (65.7%) and noncompliance with administration sequences during chemotherapy administration (50.5%) were the most common errors. The most common estimated average monthly error was not following the administration sequence of the chemotherapeutic agents (4.1 times/month, range 1-20). The most important underlying reasons for medication errors were heavy workload (49.7%) and insufficient number of staff (36.5%). Conclusions: Our findings suggest that the probability of medication error is very high during chemotherapy preparation and administration, the most common involving prescribing and ordering errors. Further studies must address the strategies to minimize medication error in chemotherapy receiving patients, determine sufficient protective measures and establishing multistep control mechanisms.

The prognosis of primary small cell carcinoma of the breast largely depends on the initial stage of the disease. Multimodality treatment including surgery, radiotherapy and chemotherapy seems to be the most appropriate strategy for early disease. Chemotherapy is usually unsuccessful in treating metastatic disease.

MA plus meloxicam or EPA supplement plus meloxicam may be effective treatment options in the management of cancer cachexia. The combined use of these agents does not provide further advantages.

Our findings suggest that c-Met immunohistochemical expression is an independent predictor of outcomes in patients with GBM treated by standard of care.

Our results suggest that c-erbB-2 overexpression may have a prognostic significance in patients with metastatic gastric cancer.

Purpose: The aim of the study was to investigate the association between the molecular subtypes and patterns of relapse in breast cancer patients who had undergone curative surgery. Methods: We retrospectively evaluated 1,350 breast cancer patients with relapses after curative surgery between 1998 and 2012 from referral centers in Turkey. Patients were divided into 4 biological subtypes according to immunohistochemistry and grade: triple negative, HER2 overexpressing, luminal A and luminal B. Results: The percentages of patients with luminal A, luminal B, HER2-overexpressing, and triple-negative breast cancer were 32.9% (n = 444), 34.9% (n = 471), 12.0% (n = 162), and 20.2% (n = 273), respectively. The distribution of metastases differed among the subgroups: bone (66.2% and 53.9% in luminal A and B vs. 38.9% in HER2-overexpressing and 45.1% in triple negative, p < 0.001), liver (40.1% in HER2-overexpressing vs. 24.5% in luminal A, 33.5% in luminal B, and 27.5% in triple negative, p < 0.001), lung (41.4% in triple negative and 35.2% in HER2-overexpressing vs. 30.2% and 30.6% in luminal A and B, p = 0.008) and brain (25.3% in HER2-overexpressing and 23.1% in triple negative vs. 10.1% and 15.1% in luminal A and B, p < 0.001). Conclusions: Organ-specific metastasis may depend on the molecular subtype of breast cancer. Tailored strategies against distant metastasis concerning the molecular subtypes in breast cancer should be considered.