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Clinical guidelines for ovarian cancer: the Korean Society of Gynecologic Oncology guidelines
Get PDFSince the latest practice guidelines for ovarian cancer were developed by the Korean Society of Gynecologic Oncology (KSGO) in 2021, many studies have examined the efficacy and safety of various treatments for epithelial ovarian cancer (EOC). Therefore, the need to develop recommendations for EOC treatments has been raised. This study searched the literature using 4 key items and the Population, Intervention, Comparison, and Outcome: the efficacy and safety of poly-ADP ribose polymerase inhibitors in newly diagnosed advanced EOC; the efficacy and safety of intraperitoneal plus intravenous chemotherapy in optimally debulked advanced EOC; the efficacy and safety of secondary cytoreductive surgery in platinum-sensitive recurrent ovarian cancer; and the efficacy and safety of the addition of bevacizumab to platinum-based chemotherapy in first platinum-sensitive recurrent EOC patients who received prior bevacizumab. The evidence for these recommendations, according to each key question, was evaluated using a systematic review and meta-analysis. The committee of ovarian cancer of the KSGO developed updated guidelines for treatments of EOC
Treatment Patterns and Prognosis of Palliative Chemotherapy Combined With Targeting Agents in Patients With Unresectable Metastatic Colorectal Cancer: CHOICE, A Multicenter Longitudinal Observational Study
No full textBACKGROUND/AIM: This study investigated the treatment patterns and prognosis of patients with metastatic or unresectable colorectal cancer (mCRC) treated with chemotherapy with targeting agents. PATIENTS AND METHODS: This longitudinal multicenter study included 963 patients with mCRC who were treated in Korea between 2016 and 2020. Treatment patterns and efficacy were compared according to the mutation status and clinical factors. RESULTS: As first-line therapy, most of the patients (83.5%) received FOLFOX plus bevacizumab (35.4%), followed by FOLFIRI plus bevacizumab (18.8%), FOLFIRI plus cetuximab (17.0%), and FOLFOX plus cetuximab (12.3%). Bevacizumab was the most frequent agent (78.8%) combined with chemotherapy in RAS-mutated CRC, while cetuximab (57.2%) in RAS wild-type CRC. Cetuximab was frequently combined with a doublet regimen in patients with left-sided CRC than in those with right-sided CRC (34.4% vs. 16%). As second-line therapy, most patients (63.4%) also received doublet regimens with bevacizumab, and FOLFIRI plus aflibercept was administered in 15.1%. The objective response rate with FOLFIRI plus cetuximab was significantly higher in patients with left-sided CRC than in those with right-sided CRC (59.2% vs. 30.8%, p=0.008) and marginally higher in patients with RAS wild-type CRC than in those with RAS-mutated CRC (55.6% vs. 0.0%, p=0.092). Progression-free survival (PFS) with FOLFOX plus bevacizumab was significantly shorter than that with FOLFIRI plus bevacizumab (p=0.030) in RAS-mutated CRC, whereas there were no significant differences between regimens in RAS wild-type CRC. CONCLUSION: In patients with unresectable metastatic colorectal cancer, doublet chemotherapy with targeting agents is the most common therapy and efficacy depends on the mutation status as well as clinical factors
The Impact of Statins on the Survival of Patients with Advanced Hepatocellular Carcinoma Treated with Sorafenib or Lenvatinib
Get PDFWe aimed to evaluate the survival benefits of coadministering statins and multityrosine kinase inhibitors (TKIs) in patients with advanced hepatocellular carcinoma (HCC). Data from the Health Insurance Review and Assessment Service in Korea (2010–2020) were utilized. Statin use (≥28 cumulative defined daily doses) was analyzed, with 1534 statin users matched to 6136 non-users (1:4 ratio) using propensity scores. Primary and secondary outcomes were overall survival (OS) and progression-free survival (PFS). Statin use significantly improved OS (hazard ratio [HR] 0.77, 95% confidence interval [CI] 0.72–0.82, p < 0.001) and PFS (HR 0.78, 95% CI 0.74–0.84, p < 0.001). Continuous or post-TKI statin users had better OS, while discontinuation after TKI use led to poorer OS. Both lipophilic and hydrophilic statins improved OS and PFS, particularly with ≥730 cumulative defined daily doses. In conclusion, combining statins and TKIs in patients with advanced HCC yielded significant survival benefits, influenced by statin dosage and duration. Continuous statin administration post-TKI treatment is crucial for improving outcomes in patients with HCC
Factors Predicting Subjective Satisfaction for Successful Hearing Aid Adaptation
Get PDF(1) Background: For successful hearing aid (HA) use during daily life, an objective parameter reflecting the subjective satisfaction is required. We explored the aided hearing status, hearing in noise test (HINT) scores, and subjective outcomes to predict performance improvements in everyday living. (2) Methods: A total of 406 patients with hearing loss (HL) who were prescribed HAs were included and were divided into two groups according to the symmetricity of HL. The relationship between audiometric data and subjective questionnaires under unaided and aided (3 months) conditions were investigated. (3) Results: Patients with symmetric HL showed a significant HINT signal-to-noise ratio (SNR) change and significant increase in their subjective satisfaction questionnaire score under the bilateral HA condition. On the other hand, the HINT SNR change and subjective questionnaire score showed various significances according to the side of HA (better or worse hearing) in asymmetric HL HINT SNR and was significantly correlated with the subjective questionnaire score in symmetric HL patients and AHL patients with unilateral HA in their better ear. (4) Conclusions: The HINT SNR improvement after long-term HA use could be an effective tool for predicting the subjective satisfaction of HA use and HA validation
Author Correction: The prediction of sagittal chin point relapse following two‑jaw surgery using machine learning
Get PDFInflamed immune phenotype predicts favorable clinical outcomes of immune checkpoint inhibitor therapy across multiple cancer types
Get PDFBackground: The inflamed immune phenotype (IIP), defined by enrichment of tumor-infiltrating lymphocytes (TILs) within intratumoral areas, is a promising tumor-agnostic biomarker of response to immune checkpoint inhibitor (ICI) therapy. However, it is challenging to define the IIP in an objective and reproducible manner during manual histopathologic examination. Here, we investigate artificial intelligence (AI)-based immune phenotypes capable of predicting ICI clinical outcomes in multiple solid tumor types.
Methods: Lunit SCOPE IO is a deep learning model which determines the immune phenotype of the tumor microenvironment based on TIL analysis. We evaluated the correlation between the IIP and ICI treatment outcomes in terms of objective response rates (ORR), progression-free survival (PFS), and overall survival (OS) in a cohort of 1,806 ICI-treated patients representing over 27 solid tumor types retrospectively collected from multiple institutions.
Results: We observed an overall IIP prevalence of 35.2% and significantly more favorable ORRs (26.3% vs 15.8%), PFS (median 5.3 vs 3.1 months, HR 0.68, 95% CI 0.61 to 0.76), and OS (median 25.3 vs 13.6 months, HR 0.66, 95% CI 0.57 to 0.75) after ICI therapy in IIP compared with non-IIP patients, respectively (p<0.001 for all comparisons). On subgroup analysis, the IIP was generally prognostic of favorable PFS across major patient subgroups, with the exception of the microsatellite unstable/mismatch repair deficient subgroup.
Conclusion: The AI-based IIP may represent a practical, affordable, clinically actionable, and tumor-agnostic biomarker prognostic of ICI therapy response across diverse tumor types
Performance of ECG-Derived Digital Biomarker for Screening Coronary Occlusion in Resuscitated Out-of-Hospital Cardiac Arrest Patients: A Comparative Study between Artificial Intelligence and a Group of Experts
Get PDFAcute coronary syndrome is a significant part of cardiac etiology contributing to out-of-hospital cardiac arrest (OHCA), and immediate coronary angiography has been proposed to improve survival. This study evaluated the effectiveness of an AI algorithm in diagnosing near-total or total occlusion of coronary arteries in OHCA patients who regained spontaneous circulation. Conducted from 1 July 2019 to 30 June 2022 at a tertiary university hospital emergency department, it involved 82 OHCA patients, with 58 qualifying after exclusions. The AI used was the Quantitative ECG (QCG™) system, which provides a STEMI diagnostic score ranging from 0 to 100. The QCG score’s diagnostic performance was compared to assessments by two emergency physicians and three cardiologists. Among the patients, coronary occlusion was identified in 24. The QCG score showed a significant difference between occlusion and non-occlusion groups, with the former scoring higher. The QCG biomarker had an area under the curve (AUC) of 0.770, outperforming the expert group’s AUC of 0.676. It demonstrated 70.8% sensitivity and 79.4% specificity. These findings suggest that the AI-based ECG biomarker could predict coronary occlusion in resuscitated OHCA patients, and it was non-inferior to the consensus of the expert group
The surgical outcomes of anterior segmental osteotomy in Asian skeletal class II patients
No full textPurpose: Anterior segmental osteotomy (ASO) following the surgery-first approach is a long-established treatment modality to resolve lip protrusion in patients with skeletal class II patterns. However, the indications and effectiveness of ASO still remain uncertain. The objective of this study is to investigate the effectiveness of ASO in Asian skeletal class II patients by evaluating the skeletal and soft tissue changes and analyzing pre-treatment variables that determine successful outcomes in occlusal as well as esthetic aspects. Methods: The lateral cephalograms of 44 skeletal class II patients who underwent ASO and orthodontic treatment for resolving lip protrusion were retrospectively collected. Hard and soft tissue variables of two groups, normalized (NG) and unnormalized (UNG) ANB after treatment were compared and analyzed. The rotational effect of the anterior segment on the hard and soft tissue was also investigated. Results: ASO was successful in correcting the skeletal class II relationship and lip protrusion (ΔANB − 2.3°, 4–5 mm lips retraction) in most cases. However, for patients with severely camouflaged skeletal class II incisors involving a large ANB and SNA, a large ANB still remained post-treatment. The study also found that rotation of the upper and lower anterior segments further augmented the amount of lip retraction. Conclusions: ASO was found to successfully correct ANB of skeletal class II patients under the following conditions (ANB 5.3° ± 1.5°, SNB 77.3° ± 4.5°, U1 to FH 115° ± 7.5, L1 to FH 48.0° ± 4.6). However, patients with larger ANB and SNA values may require bi-maxillary surgery. In addition, ASO has limitations in correcting gummy smile in cases of extreme maxillary excess. For patients requiring a large amount of lip retraction, rotation of the anterior segment may be beneficial in conjunction with bi-maxillary surgery
Applicable Machine Learning Model for Predicting Contrast-induced Nephropathy Based on Pre-catheterization Variables
Get PDFObjective Contrast agents used for radiological examinations are an important cause of acute kidney injury (AKI). We developed and validated a machine learning and clinical scoring prediction model to stratify the risk of contrast-induced nephropathy, considering the limitations of current classical and machine learning models. Methods This retrospective study included 38,481 percutaneous coronary intervention cases from 23,703 patients in a tertiary hospital. We divided the cases into development and internal test sets (8:2). Using the development set, we trained a gradient boosting machine prediction model (complex model). We then developed a simple model using seven variables based on variable importance. We validated the performance of the models using an internal test set and tested them externally in two other hospitals. Results The complex model had the best area under the receiver operating characteristic (AUROC) curve at 0.885 [95% confidence interval (CI) 0.876-0.894] in the internal test set and 0.837 (95% CI 0.819-0.854) and 0.850 (95% CI 0.781-0.918) in two different external validation sets. The simple model showed an AUROC of 0.795 (95% CI 0.781-0.808) in the internal test set and 0.766 (95% CI 0.744-0.789) and 0.782 (95% CI 0.687-0.877) in the two different external validation sets. This was higher than the value in the well-known scoring system (Mehran criteria, AUROC=0.67). The seven precatheterization variables selected for the simple model were age, known chronic kidney disease, hematocrit, troponin I, blood urea nitrogen, base excess, and N-terminal pro-brain natriuretic peptide. The simple model is available at http://52.78.230.235:8081/ Conclusions We developed an AKI prediction machine learning model with reliable performance. This can aid in bedside clinical decision making
New targets for type 2-low asthma
Get PDFAsthma is characterized by airway obstruction and inflammation, and presents significant diagnostic and treatment challenges. The concept of endotypes has improved understanding of the mechanisms of asthma and has stimulated the development of effective treatment strategies. Sputum profiles may be used to classify asthma into two major inflammatory types: type 2-high (T2H) and type 2-low (T2L) asthma. T2H, characterized by elevated type 2 inflammation, has been extensively studied and several effective biologic treatments have been developed. However, managing T2L is more difficult due to the lack of reliable biomarkers for accurate diagnosis and classification. Additionally, conventional anti-inflammatory therapy does not completely control the symptoms of T2L; therefore, further research is needed to identify effective biologic treatments. This review provides new insights into the clinical characteristics and underlying mechanisms of severe T2L and investigates potential therapeutic approaches to control the disease