Gland surgery最新文献

Background: To date, the overall survival (OS) of hormone receptor-positive advanced breast cancer (ABC) treated with palbociclib has not been reported in Chinese patients. It still remains unclear what kind of patients may benefit in OS from palbociclib treatment and what the optimal sequential antineoplastic regimen is for those progressing on palbociclib. Therefore, we aimed to investigate the OS outcome of ABC patients receiving palbociclib, establish a predictive model to identify the potential candidates who may benefit from palbociclib and explore the ideal subsequent treatment strategy after palbociclib.

Methods: This is a single-center ambispective real-world analysis of palbociclib in hormone receptor-positive ABC from April 2018 to August 2021. The patients were followed up via telephone or clinic visit. Progression-free survival (PFS), OS, overall response rate and time to second disease progression (PFS2) were evaluated as prognosis outcomes. Cyclin-dependent kinases 4/6 inhibitor (CDKI) score was established to predict OS benefit on the basis of tumor burden, line of palbociclib treatment and tumor marker.

Results: Fifty patients were included with the median PFS of 9.57 months and the median OS of 33.60 months. Age <65 years [hazard ratio (HR) 0.33, P=0.008], lung or liver involvement (HR 3.01, P=0.005) and > first line palbociclib therapy (HR 2.13, P=0.03) were independent unfavorable prognosticators for PFS. Positive estrogen receptor (ER) (HR 0.22, P=0.004), metastatic sites <3 (HR 3.59, P=0.02), absence of lung or liver involvement (HR 3.77, P=0.058) and PFS ≥12 months during palbociclib regimen (HR 0.14, P<0.001) could predict longer OS. CDKI score discriminated OS significantly (HR 4.41, P=0.009) and the CDKI score-based models were multidimensionally verified with satisfying performance, among which the area under the curve of receiver operating characteristic reached 0.835 and the C-index was 0.72. Moreover, chemo-free regimens saw improvement in time to second disease progression (HR 0.32, P=0.006) and OS (HR 0.32, P=0.049) for patients progressing on palbociclib compared with chemotherapy-based regimens.

Conclusions: CDKI score is a practical and comprehensive tool in predicting OS benefit for ABC patients treated with palbociclib, which deserves further validation. Patients who progressed on palbociclib seem to keep benefiting from chemo-free antineoplastic treatments. These findings may help identify the candidates for CDK4/6 inhibitor and optimize the strategies for hormone receptor-positive ABC.

Background: It remains uncertain whether hand-assisted laparoscopic adrenalectomy (HAL) has advantages in treating large pheochromocytomas (PHEOs). This study aimed to assess the feasibility and safety of HAL compared to laparoscopic adrenalectomy (LA).

Methods: We conducted a retrospective study on patients with PHEOs ≥6 cm who received HAL (n=16) and LA (n=20) at Shandong Provincial Hospital from January 2020 to January 2023. The two groups were balanced into 8 pairs using propensity score matching (PSM). Perioperative parameters and long-term follow-up outcomes were compared between the two groups.

Results: After adjusting for balance through PSM, patients in the HAL group had shorter operation time (105.00±18.52 vs. 147.50±7.07 minutes, P<0.001), faster bowel recovery days (1.0 vs. 2.0 days, P=0.043), and shorter postoperative hospital stays (5.00 vs. 7.50 days, P=0.01). The differences in blood pressure improvement within 3 months postoperatively, and recurrence and metastasis between the two groups (75.00% vs. 62.50%, P>0.99; 12.50% vs. 12.50%, P>0.99) were not statistically significant.

Conclusions: This study suggested that HAL was feasible and safe for patients with large PHEOs. Both HAL and LA showed comparable perioperative and long-term follow-up results.

Background: The status of central lymph node (CLN) is a crucial determinant for the initial treatment of papillary thyroid cancer (PTC), but preoperative ultrasound (US) has limited ability to accurately assess their condition. This study aimed to develop a risk score model for risk stratification of CLN metastasis in unifocal PTC patients to guide the initial treatment.

Methods: A total of 5,374 patients diagnosed with unifocal PTC at Union Hospital between November 2009 and August 2022 were finally enrolled in the analysis, including 3,542 patients in derivation cohort and 1,832 patients in validation cohort. Stepwise multivariable logistic regression was used to build the risk score of CLN metastasis. Risk score weights were assigned by dividing the coefficients of the predictors with the lowest coefficient value in the final model and rounding to the nearest integer. Points were calculated for each patient by adding these weights.

Results: Ten multivariable predictors constructed the final model, including age, gender, body mass index, Hashimoto's disease, tumor location, calcification, capsule abnormalities, CLN and lateral lymph node (LN) abnormalities and tumor size. Based on the scores derived from these variables, patients were classified into four risk categories: low [0-9], low to intermediate [10-13], intermediate to high [14-17] and high [≥18], corresponding to 20.34%, 37.42%, 59.65%, and 83.82% of the observed incidence of CLN metastasis in the derivation cohort, respectively. In derivation and validation cohorts, the area under the curve of the final model was 0.764 and 0.72, respectively.

Conclusions: Compared to relying solely on tumor size and LNs US findings, our risk score, incorporating demographic characteristics and routine pre-operative examinations, served as a more practical and effective tool for risk stratification of CLN metastasis in unifocal PTC patients, facilitating in clinical decision-making.

Background: Differentiated thyroid cancer (DTC) progresses slowly, but patients with lung metastasis (LM) have a poor prognosis. The aim of this study was to develop and evaluate the predictive ability of machine learning (ML) models in estimating the risk of LM in patients with DTC and to identify the independent risk factors specific to different age and gender subgroups.

Methods: The demographic and clinicopathological data of patients with DTC were obtained from two databases: firstly, the National Institutes of Health Surveillance, Epidemiology, and End Results (SEER) database [2010-2015], which provides extensive epidemiological and clinical information on cancer patients; secondly, the Zhangzhou Municipal Hospital Affiliated to Fujian Medical University [2014-2017], which focuses more on patients' specific clinicopathological characteristics and treatment outcomes. Common variables from both databases were extracted. The data were then split into training, testing and validation sets. The training set was used to build and train ML models, while the testing and validation set were employed to assess the performance of these models. In terms of model development, we established five different ML models: logistic regression (LR), random forest (RF), decision tree (DT), extreme gradient boosting (XGBoost), and gradient boosting machine (GBM). For model validation, we utilized various evaluation metrics, including accuracy, precision, recall, F1 score, Brier score, area under the receiver operating characteristic (ROC) curve (AUROC), area under the precision-recall (PR) curve (PR-AUC), calibration curve, and decision curve analysis (DCA). The importance of various features was ranked and visualized for the top-performing models.

Results: The analysis identified age, gender, tumor size, T stage, N stage, and histologic type as significant independent risk factors for LM. The effects of gender, T stage, and histological type on the risk of LM varied across the different age subgroups. In the female population, tumor size was an independent risk factor for LM, while it was not in the male population. GBM achieved an AUROC of 0.982, a Brier score of 0.047, an accuracy of 0.818, and an F1 score of 0.818 in the validation set, outperforming the other models.

Conclusions: The GBM model emerged as an effective tool for identifying high-risk LM populations in DTC, with the potential to guide clinical practice and facilitate the development of individualized treatment plans. Further research to validate these findings across more diverse patient populations and clinical settings is recommended.

Background: Transoral endoscopic resection is an updated treatment of accessory parotid gland tumors. The aim of this study was to present the endoscopic transoral resection surgical technique and clinical outcomes of accessory parotid tumors.

Methods: Articles on endoscopic transoral approach for accessory parotid tumors were searched in PubMed, China National Knowledge Infrastructure (CNKI), and Web of Science databases. Patient information from these articles was extracted and retrospectively analyzed along with data from patients we treated. The procedure was reported in detail using a classic case.

Results: A total of 119 articles were identified through database searches, of which 7 were included in the final analysis, providing medical information for 30 patients. Additionally, 10 cases of endoscopic transoral surgery were performed at West China Hospital of Stomatology and the First Affiliated Hospital of Xiamen University from January 2022 to April 2024. There are five male patients and five female patients, with a mean age of 42.50±15.56 years. The average operation time was 54.70±7.73 minutes. Lesion diameters varied from 1 to 3 cm, averaging 1.90±0.57 cm. Most patients were diagnosed with pleomorphic adenoma. One patient was diagnosed with mucoepidermoid carcinoma according to intraoperative frozen biopsy, and a complete parotid lobectomy was performed with traditional standard S-shaped incision instead. All of the 40 patients were aesthetically satisfied during postoperative follow-up, with only five patients reporting postoperative complications: swelling, hydrops, and transient facial palsy.

Conclusions: The endoscopic transoral approach to accessory parotid tumors avoids external facial scars and offers good aesthetic outcomes.

Background: Observational studies have suggested an association between thyroid volume changes and thyroid disease, but the causal relationship and direction of these effects remain unclear. This study employs a two-sample Mendelian randomization (MR) approach to assess the effect of thyroid volume on clinically common benign and malignant thyroid diseases.

Methods: Summary data from genome-wide association studies (GWAS) were utilized for secondary data analysis to investigate the link between thyroid volume and disease. Gene loci strongly associated with thyroid volume were selected as the instrumental variables. Five complementary two-sample MR methods were used to evaluate the causal effect of thyroid volume on thyroid diseases and thyroid stimulating hormone (TSH).

Results: Thyroid volume was found to be significantly associated with autoimmune thyroid disease [odds ratio (OR) =1.045; 95% confidence interval (CI): 1.022-1.069; P<0.001], Hashimoto's thyroiditis (OR =1.800; 95% CI: 1.167-2.778; P=0.008), Graves' disease (OR =0.136; 95% CI: 0.065-0.282; P<0.001), hyperthyroidism (OR =1.011; 95% CI: 1.008-1.014; P<0.001), multinodular goiters (OR =121.541; 95% CI: 23.323-633.378; P<0.001), non-toxic single thyroid nodules (OR =7.536; 95% CI: 2.280-24.911; P<0.001), benign thyroid neoplasms (OR =4.300; 95% CI: 1.170-15.802; P=0.03), and TSH levels (OR =0.401; 95% CI: 0.247-0.652; P<0.001). Thyroid volume was negatively associated with thyroid carcinomas (OR =0.401; 95% CI: 0.208-0.772; P=0.006; β =-0.915).

Conclusions: Our study found that there is a causal relationship between thyroid volume and some thyroid diseases, and that increased thyroid volume levels exert protective effects on thyroid carcinoma. Monitoring thyroid volume may be of value in the prevention of clinical thyroid diseases.

Background: Metastatic prostate cancer (mPCa) complicates treatment due to its unpredictable progression. Current prognostic tools often lack precision. This study aimed to develop an effective tool to predict overall survival (OS) in mPCa patients undergoing radiotherapy, thereby addressing the clinical need for personalized treatment decisions.

Methods: A total of 1,171 mPCa patients receiving radiotherapy between 2004 and 2015 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Patients with distant metastases and complete data on prostate-specific antigen (PSA), Gleason score (GS), and tumor-node-metastasis (TNM) staging were included. The cohort was randomly divided into a training set (n=819) and an internal validation set (n=352). Independent prognostic factors, including age, marital status, PSA, GS, T-stage, M-stage, and chemotherapy, were used to construct a nomogram. The external validation cohort comprised 138 mPCa patients from The First Affiliated Hospital of Nanchang University, with survival outcomes followed through their medical records.

Results: In the SEER cohort, 67.7% of patients were married, 74.3% were White, and 23.2% had a GS of 7. The external validation cohort had a mean survival of 45.8 months. The nomogram's area under the curve (AUC) values for predicting 1-, 3-, and 5-year OS were 0.686, 0.679, and 0.724 in the training cohort; 0.713, 0.732, and 0.711 in the internal validation cohort; and 0.748, 0.735, and 0.750 in the external validation cohort, respectively. Calibration plots demonstrated reasonable agreement between predicted and observed survival rates, but the AUC values indicate moderate predictive performance.

Conclusions: Although the nomogram offers some clinical value in estimating survival for mPCa patients receiving radiotherapy, its predictive accuracy remains moderate. Further refinements incorporating additional prognostic factors may enhance its clinical utility.

Background: Sentinel lymph node biopsy (SNB) using radioisotopes is a standard method for assessing axillary lymph node status in patients with breast cancer. Although preoperative lymphoscintigraphy can estimate the number of sentinel lymph nodes (SNs), multiple radioactive SNs are often identified, even when lymphoscintigraphy reveals only one SN. Importantly, metastases are not always observed in the most radioactive SN (hottest SN). This study aimed to determine the significance of metastases in the second or less radioactive SNs when the hottest SN is negative.

Methods: We retrospectively analyzed 114 patients with breast cancer with positive SNs who underwent axillary lymph node dissection. The clinicopathological characteristics, SN radioactivity, and axillary lymph node status were evaluated.

Results: Twenty-six patients exhibited metastasis in the second or less radioactive SNs without metastasis in the hottest SN. These patients had a lower risk of non-SN metastasis compared with those with metastasis to the hottest SN (P=0.03). Multivariate analysis identified metastasis in the hottest SN [hazard ratio (HR) 4.93, P=0.01] and the detection of ≥2 SNs by lymphoscintigraphy (HR 3.36, P=0.01) as independent predictors of non-SN metastasis. None of the patients with only one lymph node detected by lymphoscintigraphy and metastasis to the second or less SNs without metastasis to the hottest SN showed non-SN metastasis.

Conclusions: Patients with metastasis in the second or less radioactive SNs, but not in the hottest SN, have a lower risk of non-SN metastasis than those with a positive hottest SN. Combining radioactivity with lymphoscintigraphic information can enhance the accuracy of non-SN status prediction.