A 35-year-old woman underwent laparoscopic radical hysterectomy, pelvic lymphadenectomy and ovarian transposition for stage IB2 cervical adenocarcinoma. She received adjuvant concurrent chemoradiation for poor pathologic risk factors but had tumor recurrence 20 months after the surgery. Transposed ovaries were uninvolved in the recurrence and progression. Salvage chemotherapy and radiotherapy were given. Despite systemic chemotherapy and repeat pelvic radiotherapy, the patient was able to maintain ovarian function. Ovarian transposition in cervical cancer is an easily performed procedure that does not alter the prognosis of the disease in some cases. Present recommendations for its use should be reevaluated so that more premenopausal cancer patients may benefit from this underutilized procedure.
Adenocarcinoma ; Female ; Humans ; Hysterectomy ; Laparoscopy ; Lymph Node Excision ; Ovary ; Prognosis ; Quality of Life ; Recurrence ; Risk Factors ; Uterine Cervical Neoplasms

OBJECTIVEAccuracy of diagnostic methods for detecting Helicobacter pylori (H. pylori) infection among patients with bleeding peptic ulcers has not been thoroughly investigated. The aim of this study was to compare the diagnostic tests and their combined usage in detection of H. pylori infection in patients with bleeding gastric ulcers and without the use of nonsteroidal anti-inflammatory drugs.

METHODSA total of 57 patients who presented with bleeding gastric ulcers by endoscopy were enrolled. The status of H. pylori was identified by performing the rapid urease test (RUT), histology and (13)C-labeled urea breath test (UBT). The criteria for having H. pylori infection was a minimum of two positive tests.

RESULTSThe prevalence of H. pylori infection in our patient group was 80.7%. Among the three tests used: RUT, histology, and UBT, sensitivities were 56.5%, 97.8% and 100%, while specificities were 100%, 45.5% and 81.8%, respectively. The overall accuracies of the tests were 78.3%, 71.6% and 90.9%, respectively. Although UBT obtained significantly higher accuracy than histology (P = 0.02) as opposed to RUT (P = 0.11), UBT had significantly higher sensitivity than RUT (P < 0.001). In terms of combining any two of the three tests, more accuracy (98.9%) was achieved when both UBT and histology were used to confirm the diagnosis of the other. Conversely, failure to use combined tests generated the potential of missing a proper H. pylori diagnosis.

CONCLUSIONSUBT is superior to the other two tests in bleeding gastric ulcers. RUT lacks sensitivity for detection of H. pylori infection. However, the concomitant use of UBT and histology seems to be more accurate when gastric ulcers present with bleeding.

Adolescent ; Adult ; Aged ; Aged, 80 and over ; Breath Tests ; Female ; Helicobacter Infections ; diagnosis ; pathology ; Helicobacter pylori ; Humans ; Male ; Middle Aged ; Peptic Ulcer Hemorrhage ; complications ; Sensitivity and Specificity ; Stomach Ulcer ; complications ; Urea

Background/Aims: Direct‐acting antivirals (DAAs) have been approved for hepatitis C virus (HCV) treatment in patients with end-stage renal disease (ESRD) on hemodialysis. Nevertheless, the complicated comedications and their potential drug-drug interactions (DDIs) with DAAs might limit clinical practice in this special population. Methods: The number, class, and characteristics of comedications and their potential DDIs with five DAA regimens were analyzed among HCV-viremic patients from 23 hemodialysis centers in Taiwan. Results: Of 2,015 hemodialysis patients screened in 2019, 169 patients seropositive for HCV RNA were enrolled (mean age, 65.6 years; median duration of hemodialysis, 5.8 years). All patients received at least one comedication (median number, 6; mean class number, 3.4). The most common comedication classes were ESRD-associated medications (94.1%), cardiovascular drugs (69.8%) and antidiabetic drugs (43.2%). ESRD-associated medications were excluded from DDI analysis. Sofosbuvir/velpatasvir/voxilaprevir had the highest frequency of potential contraindicated DDIs (red, 5.6%), followed by glecaprevir/pibrentasvir (4.0%), sofosbuvir/ledipasvir (1.3%), sofosbuvir/velpatasvir (1.3%), and elbasvir/grazoprevir (0.3%). For potentially significant DDIs (orange, requiring close monitoring or dose adjustments), sofosbuvir/velpatasvir/voxilaprevir had the highest frequency (19.9%), followed by sofosbuvir/ledipasvir (18.2%), glecaprevir/pibrentasvir (12.6%), sofosbuvir/velpatasvir (12.6%), and elbasvir/grazoprevir (7.3%). Overall, lipid-lowering agents were the most common comedication class with red-category DDIs to all DAA regimens (n=62), followed by cardiovascular agents (n=15), and central nervous system agents (n=10). Conclusions HCV-viremic patients on hemodialysis had a very high prevalence of comedications with a broad spectrum, which had varied DDIs with currently available DAA regimens. Elbasvir/grazoprevir had the fewest potential DDIs, and sofosbuvir/velpatasvir/voxilaprevir had the most potential DDIs.

Background/Aims: Chronic hepatitis C (CHC) patients who failed antiviral therapy are at increased risk for hepatocellular carcinoma (HCC). This study assessed the potential role of metformin and statins, medications for diabetes mellitus (DM) and hyperlipidemia (HLP), in reducing HCC risk among these patients. Methods: We included CHC patients from the T-COACH study who failed antiviral therapy. We tracked the onset of HCC 1.5 years post-therapy by linking to Taiwan’s cancer registry data from 2003 to 2019. We accounted for death and liver transplantation as competing risks and employed Gray’s cumulative incidence and Cox subdistribution hazards models to analyze HCC development. Results: Out of 2,779 patients, 480 (17.3%) developed HCC post-therapy. DM patients not using metformin had a 51% increased risk of HCC compared to non-DM patients, while HLP patients on statins had a 50% reduced risk compared to those without HLP. The 5-year HCC incidence was significantly higher for metformin non-users (16.5%) versus non-DM patients (11.3%; adjusted sub-distribution hazard ratio [aSHR]=1.51; P=0.007) and metformin users (3.1%; aSHR=1.59; P=0.022). Statin use in HLP patients correlated with a lower HCC risk (3.8%) compared to non-HLP patients (12.5%; aSHR=0.50; P<0.001). Notably, the increased HCC risk associated with non-use of metformin was primarily seen in non-cirrhotic patients, whereas statins decreased HCC risk in both cirrhotic and non-cirrhotic patients. Conclusions Metformin and statins may have a chemopreventive effect against HCC in CHC patients who failed antiviral therapy. These results support the need for personalized preventive strategies in managing HCC risk.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.