Carcinogenesis and tumor growth are associated with chronic inflammation and the host immune system. Here, we investigated the clinical significance and relationship between tumor-infiltrating lymphocytes (TILs) and hematologic parameters in patients with breast cancer. Invasive ductal breast cancer patients (N = 145) who underwent surgery were retrospectively evaluated. Samples were obtained using a core needle biopsy for CD8+, FOXP3+ TIL assessment. Blood lymphocytes, neutrophils, monocytes, and platelets were obtained by peripheral venous punctures. CD8 + TILs were significantly associated with absolute lymphocyte count (ALC) and the absolute monocyte count (AMC). Low LMR (ALC/AMC) (cut-off - 5.3, range = 0.73–12.31) was associated with poor overall survival (OS) (p = 0.010), disease-free survival (DFS) (p = 0.005). However, in subgroup analysis, LMR did not have any value as a prognostic factor in HER2-positive breast cancers. TILs had different prognostic impacts across breast cancer subtypes, although they were not statistically significant. The treatment response after NAC tended to improve in breast cancer patients with high FOXP3+ TILs, low NLR (neutrophil count/ALC) (FOXP3 p for trend = 0.006, NLR p for trend = 0.063). A relevance between TILs and hematologic parameters in breast cancer was demonstrated. The influence of the immune system on breast cancer progression may differ by subtype.

Background: The aim of this study is to compare the feasibility and oncologic safety of Single–incision, gasless, Endoscopic trans-axillary bilateral Total thyroidectomy (SET) with open cervical total thyroidectomy in patients with papillary thyroid carcinoma (PTC). Materials and Methods: From March 2008 to December 2012, PTC patients underwent bilateral total thyroidectomy. Conventional, open surgery was performed on 538 patients (Group O) and endoscopic surgery was performed on 200 patients (Group E). We analyzed the patient's clinicopathologic, postoperative complications, and surgical completeness. Results: The mean ages of the patients were 48.9 ± 0.5 (range = 24–77) in Group O and 39.5 ± 0.8 (range = 17–73) in Group E with statistical significance (P < .001). Percentage of female patients were 74.3% in Group O and 96.0% in Group E with statistical significance (P < .001). The postoperative hospital stay in Group O was significantly longer than Group E (4.60 ± 0.05 versus 3.30 ± 0.05; P < .001). The operation time in Group E was significantly longer than Group O (93.9 ± 1.3 versus 142.6 ± 3.3; P < .001). More transient hypocalcemia was found in Group O compared to Group E with statistical significance (28.1% versus 22.4%; P < .001). There were no significant differences with respect to permanent hypocalcemia, permanent recurrent laryngeal nerve palsy, seroma, and hematoma. The mean 1 year-stimulated sTg was 0.23 ± 0.03 and 0.18 ± 0.02 in Group O and E, respectively. Tumor recurrence during short-term follow-up at neck ultrasonography (1 year) was detected in 4 patients in Group O. Conclusion: SET is safe and effective, not only for low-risk patients with early-detected cancer, but also for selected cases of advanced cancer.

Background: Artificial intelligence (AI) algorithms for the independent assessment of screening mammograms have not been well established in a large screening cohort of Asian women. We compared the performance of screening digital mammography considering breast density, between radiologists and AI standalone detection among Korean women. Methods: We retrospectively included 89,855 Korean women who underwent their initial screening digital mammography from 2009 to 2020. Breast cancer within 12 months of the screening mammography was the reference standard, according to the National Cancer Registry. Lunit software was used to determine the probability of malignancy scores, with a cutoff of 10% for breast cancer detection. The AI’s performance was compared with that of the final Breast Imaging Reporting and Data System category, as recorded by breast radiologists. Breast density was classified into four categories (A–D) based on the radiologist and AI-based assessments. The performance metrics (cancer detection rate [CDR], sensitivity, specificity, positive predictive value [PPV], recall rate, and area under the receiver operating characteristic curve [AUC]) were compared across breast density categories. Results: Mean participant age was 43.5 ± 8.7 years; 143 breast cancer cases were identified within 12 months. The CDRs (1.1/1000 examination) and sensitivity values showed no significant differences between radiologist and AI-based results (69.9% [95% confidence interval [CI], 61.7–77.3] vs. 67.1% [95% CI, 58.8–74.8]). However, the AI algorithm showed better specificity (93.0% [95% CI, 92.9–93.2] vs. 77.6% [95% CI, 61.7–77.9]), PPV (1.5% [95% CI, 1.2–1.9] vs. 0.5% [95% CI, 0.4–0.6]), recall rate (7.1% [95% CI, 6.9–7.2] vs. 22.5% [95% CI, 22.2–22.7]), and AUC values (0.8 [95% CI, 0.76–0.84] vs. 0.74 [95% CI, 0.7–0.78]) (all P < 0.05). Radiologist and AI-based results showed the best performance in the non-dense category; the CDR and sensitivity were higher for radiologists in the heterogeneously dense category (P = 0.059). However, the specificity, PPV, and recall rate consistently favored AI-based results across all categories, including the extremely dense category. Conclusions: AI-based software showed slightly lower sensitivity, although the difference was not statistically significant. However, it outperformed radiologists in recall rate, specificity, PPV, and AUC, with disparities most prominent in extremely dense breast tissue.

Nipple sparing mastectomy provides good cosmetic results and low local recurrence rates for breast cancer patients. However, there is a potential risk of leaving an occult tumor within the nipple, which could lead to cancer relapse and poor prognosis for the patient. The objective of this study was to investigate the occult nipple involvement rate in mastectomy specimens, and to identify preoperative magnetic resonance imaging (MRI) findings and the clinicopathological characteristics of the primary tumor that may correlate with nipple invasion. Four hundred sixty-six consecutive mastectomy samples with grossly unremarkable nipples were evaluated. Demographic and clinicopathological data were collected. Nipple involvement was evaluated using serial histological sections. The tumor size and tumor-nipple distance were measured using preoperative MRI images. Thirty-six of the 466 therapeutic mastectomy specimens (7.7%) were found to have occult nipple involvement. In univariate analysis, tumor size, tumor-nipple distance, lymph node status, p53 mutation, and lymphovascular invasion (LVI) were found to influence the likelihood of nipple involvement. Multivariate logistic regression analysis, adjusted by lymph node status, p53 mutation, and LVI, showed that tumor size and tumor-nipple distance were predictive factors indicating nipple involvement. With regard to tumor location, only tumors in the central area of the breast showed a significant association with nipple involvement. In this study, a statistically significant association was found between occult nipple involvement and tumor size, tumor-nipple distance, axillary lymph node status, LVI, and p53 mutation. A cutoff point of 2.2 cm for tumor size and 2 cm for tumor-nipple distance could be used as parameters to predict occult nipple involvement.