Assessing the relative effectiveness of various ultrasound-guided ablation techniques for treating benign thyroid nodules: A systematic review and network meta-analysis.

BACKGROUND: Benign thyroid nodules (BTNs) represent a prevalent clinical challenge globally, with various ultrasound-guided ablation techniques developed for their management. Despite the availability of these methods, a comprehensive evaluation to identify the most effective technique remains absent. This study endeavors to bridge this knowledge gap through a network meta-analysis (NMA), aiming to enhance the understanding of the comparative effectiveness of different ultrasound-guided ablation methods in treating BTNs. METHODS: We comprehensively searched PubMed, Embase, Cochrane, Web of Science, Ovid, SCOPUS, and ProQuest for studies involving 16 ablation methods, control groups, and head-to-head trials. NMA was utilized to evaluate methods based on the percentage change in nodule volume, symptom score, and cosmetic score. This study is registered in INPLASY (registration number 202260061). RESULTS: Among 35 eligible studies involving 5655 patients, NMA indicated that RFA2 (radiofrequency ablation, 2 sessions) exhibited the best outcomes at 6 months for percentage change in BTN volume (SUCRA value 74.6), closely followed by RFA (SUCRA value 73.7). At 12 months, RFA was identified as the most effective (SUCRA value 81.3). Subgroup analysis showed RFA2 as the most effective for solid nodule volume reduction at 6 months (SUCRA value 75.6), and polidocanol ablation for cystic nodules (SUCRA value 66.5). CONCLUSION: Various ablation methods are effective in treating BTNs, with RFA showing notable advantages. RFA with 2 sessions is particularly optimal for solid BTNs, while polidocanol ablation stands out for cystic nodules.

Intra-arterial chemotherapy plus BCG, a promising combination adjuvant treatment for high-risk NMIBC.

PURPOSE: To develop a novel combination therapy for high-risk nonmuscle-invasive bladder cancer (NMIBC) after transurethral resection of bladder tumor (TURBT), namely, intra-arterial chemotherapy (IAC) plus BCG immunotherapy, and to compare the feasibility and safety of the 2 therapies. MATERIALS AND METHODS: A retrospective study was conducted on the data of 119 patients who were diagnosed with high-risk NMIBC and underwent TURBT in the past 5 years. Those who did not complete the treatment were excluded, and the remaining 98 patients were divided into 2 groups: both groups received intravesical BCG immunotherapy, while the BCG+IAC group received 4 courses of extra intra-arterial chemotherapy. Clinical and follow-up data were processed using statistical software. RESULTS: The recurrence rate was 22.2% in the BCG+IAC group and 35.8% in the BCG group, whereas the progression rates were 8.9% and 24.5%, respectively. In the Kaplan-Meier plot, a statistically significant difference was observed with respect to recurrence-free survival (p = 0.025), as well as the progression-free survival of the two groups was similar (p = 0.019). A total of 22.2% of the patients with adverse effects of IAC and 79.6% of patients suffered from adverse reactions to BCG immunotherapy, and most of the adverse effects were mild and tolerable. Univariate and multivariate analysis indicated that multifocal and treatment were independent risk factors for recurrence, while the history of recurrence and treatment were independent risk factors for progression. CONCLUSION: IAC could be a promising auxiliary treatment for BCG immunotherapy in decreasing the recurrence and progression rate of high-risk NMIBC with little additional toxicity.

Prognostic Value of Lymph Node Parameters in Elderly Patients With Stage III Serous Ovarian Cancer Based on Competing Risk Model.

OBJECTIVES: Competing risk models were used in this study. The purpose of this study was to assess the predictive usefulness of lymph node characteristics in elderly patients with stage III serous ovarian cancer. METHODS: We conducted a retrospective analysis on 148,598 patients from 2010 to 2016 using the surveillance, epidemiology, and end results database. Lymph node characteristics were collected and examined, including the number of lymph nodes retrieved the number of lymph nodes examined (ELN) and the number of positive lymph nodes (PN). Using competing risk models, we evaluated the connection between these variables and overall survival (OS) and disease-specific survival (DSS). RESULTS: This study included a total of 3457 ovarian cancer patients. Multivariate analysis using the COX proportional hazards model found that ELN>22 was an independent predictive factor for both OS (hazard ratio [HR] [95% CI]=0.688 [0.553 to 0.856], P <0.05) and DSS (HR [95% CI]=0.65 [0.512 to 0.826], P <0.001), PN>8 was identified as a significant risk factor for both OS (HR [95% CI]=0.908 [0.688 to 1.199], P =0.497) and DSS (HR [95% CI]=0.926 [0.684 to 1.254], P =0.62). Subsequently, using the competing risk model, ELN>22 was found to be an independent protective factor for DSS (HR [95% CI]=0.738 [0.574 to 0.949], P =0.018), while PN>8 was identified as a risk factor for DSS (HR [95% CI]=0.999 [0.731 to 1.366], P =1). CONCLUSIONS: Our findings demonstrate the robustness of the competing risk model to evaluate the results of the COX proportional hazards model analysis.

Developing and optimizing a machine learning predictive model for post-thrombotic syndrome in a longitudinal cohort of patients with proximal deep venous thrombosis.

BACKGROUND: Post-thrombotic syndrome (PTS) is the most common chronic complication of deep venous thrombosis (DVT). Risk measurement and stratification of PTS are crucial for patients with DVT. This study aimed to develop predictive models of PTS using machine learning for patients with proximal DVT. METHODS: Herein, hospital inpatients from a DVT registry electronic health record database were randomly divided into a derivation and a validation set, and four predictive models were constructed using logistic regression, simple decision tree, eXtreme Gradient Boosting (XGBoost), and random forest (RF) algorithms. The presence of PTS was defined according to the Villalta scale. The areas under the receiver operating characteristic curves, decision-curve analysis, and calibration curves were applied to evaluate the performance of these models. The Shapley Additive exPlanations analysis was performed to explain the predictive models. RESULTS: Among the 300 patients, 126 developed a PTS at 6 months after DVT. The RF model exhibited the best performance among the four models, with an area under the receiver operating characteristic curves of 0.891. The RF model demonstrated that Villalta score at admission, age, body mass index, and pain on calf compression were significant predictors for PTS, with accurate prediction at the individual level. The Shapley Additive exPlanations analysis suggested a nonlinear correlation between age and PTS, with two peak ages of onset at 50 and 70 years. CONCLUSIONS: The current predictive model identified significant predictors and accurately predicted PTS for patients with proximal DVT. Moreover, the model demonstrated a nonlinear correlation between age and PTS, which might be valuable in risk measurement and stratification of PTS in patients with proximal DVT.

Ultrasound-based radiomics score for pre-biopsy prediction of prostate cancer to reduce unnecessary biopsies.

BACKGROUND: Patients undergoing prostate biopsies (PBs) suffer from low positive rates and potential risk for complications. This study aimed to develop and validate an ultrasound (US)-based radiomics score for pre-biopsy prediction of prostate cancer (PCa) and subsequently reduce unnecessary PBs. METHODS: Between December 2015 and March 2018, 196 patients undergoing initial transrectal ultrasound (TRUS)-guided PBs were retrospectively enrolled and randomly assigned to the training or validation cohort at a ratio of 7:3. A total of 1044 radiomics features were extracted from grayscale US images of each prostate nodule. After feature selection through the least absolute shrinkage and selection operator (LASSO) regression model, the radiomics score was developed from the training cohort. The prediction nomograms were developed using multivariate logistic regression analysis based on the radiomics score and clinical risk factors. The performance of the nomograms was assessed and compared in terms of discrimination, calibration, and clinical usefulness. RESULTS: The radiomics score consisted of five selected features. Multivariate logistic regression analysis demonstrated that the radiomics score, age, total prostate-specific antigen (tPSA), and prostate volume were independent factors for prediction of PCa (all p < 0.05). The integrated nomogram incorporating the radiomics score and three clinical risk factors reached an area under the curve (AUC) of 0.835 (95% confidence interval [CI], 0.729-0.941), thereby outperforming the clinical nomogram which based on only clinical factors and yielded an AUC of 0.752 (95% CI, 0.618-0.886) (p = 0.04). Both nomograms showed good calibration. Decision curve analysis indicated that using the integrated nomogram would add more benefit than using the clinical nomogram. CONCLUSION: The radiomics score was an independent factor for pre-biopsy prediction of PCa. Addition of the radiomics score to the clinical nomogram shows incremental prognostic value and may help clinicians make precise decisions to reduce unnecessary PBs.

Impact of Time-To-Surgery on the Prognosis of Patients with T1 Renal Cell Carcinoma: Implications for the COVID-19 Pandemic.

Background: During the COVID-19 pandemic, elective surgery has to undergo longer wait times, including nephrectomy for T1 renal cell carcinoma (RCC). This study aimed to investigate the time-to-surgery (TTS) of Chinese T1 RCC patients and its influencing factors, and to illustrate the impact of TTS on the prognosis of T1 RCC. Methods: We retrospectively enrolled 762 Chinese patients with pathological T1 RCC that underwent nephrectomy. To discover the impact of TTS on survival outcomes, we explored the possible delay intervals by week using the Kaplan-Meier method and Log-rank test. Cox proportional hazard models with inverse probability-treatment weighting (IPTW) were used to assess the association between TTS and disease-free survival (DFS) and overall survival (OS). Results: The median TTS of T1 RCC patients was 15 days. The Charlson comorbidity index, the Preoperative Aspects and Dimensions Used for an Anatomical (PADUA) score, and the maximal tumor diameter on presentation were independent influencing factors for TTS. The cut-off point of TTS was selected as 5 weeks according to the Log-rank analysis. For T1a RCC, patients with TTS > 5 weeks had similar DFS (HR = 2.39; 95% CI, 0.82−6.94; p = 0.109) and OS (HR = 1.28; 95% CI, 0.23−7.16; p = 0.779) compared to patients with TTS ≤ 5 weeks. For T1b RCC, patients with TTS > 5 weeks had shorter DFS (HR = 2.90; 95% CI = 1.46−5.75; p = 0.002) and OS (HR = 2.49, 95% CI = 1.09−5.70; p = 0.030) than patients with TTS ≤ 5 weeks. Conclusions: Prolonged TTS had no impact on the prognosis of T1a RCC while surgery delayed for over 5 weeks may lead to worse survival in T1b RCC.

Light-activated gold nanorods for effective therapy of venous malformation.

Gold nanorods have been studied extensively in the field of tumor therapy but have not been explored in the treatment of venous malformation (VM), which is a common vascular disease in clinic practice lacking an effective therapeutic approach. Herein we reported a nanoplatform of CD31 antibody-conjugated gold nanorods for the photothermal therapy of venous malformation. We immobilized CD31 antibodies on gold nanorods using standard 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC)/N-hydroxysulfosuccinimide sodium (NHS) amine coupling strategies. Besides, a VM xenograft model suitable for testing therapeutic efficacy was established by isolating and culturing VM patient endothelial cells. In vitro experiments indicated that anti-CD31 gold nanorods (GNRs) combined with photothermal therapy (PTT) contributed to the suppression of proliferation and activation of the apoptosis pathway. For in vivo experiments, anti-CD31 GNRs were locally injected into VM xenograft models followed by near infrared (NIR) 808 â€‹nm laser irradiation. Notably, VM on the mice was destroyed and absorbed. The anti-CD31 GNRs nanoplatform may serve as a new strategy for the treatment of VM which is of good biosafety and high value of applications.