Association of high disease activity and serum IL-6 levels with the incidence of inflammatory major organ events in Behçet disease: a prospective registry study.

Background: Little is known about the relationship between the disease activity of Behçet disease (BD) and the incidence of inflammatory major organ events. Objectives: In this prospective registry study, we investigated the association between the Behçet Disease Current Activity Form (BDCAF) and incidence of inflammatory major organ events, defined as the inflammation of the ocular, central nervous, intestinal, and vascular systems in BD. Methods: We enrolled participants from Japanese multicenter prospective cohorts. The BDCAF was evaluated annually. BD-related symptoms, including inflammatory major organ events, were monitored. The association between BDCAF and inflammatory major organ events was analyzed by time-to-event analysis. An unsupervised clustering of the participants' BDCAF, therapeutic agents, and multiple serum cytokines was also performed to examine their association with inflammatory major organ events. Results: A total of 260 patients were included. The patients had a median BDCAF score of 2 [Interquartile range, 1-3] at the enrolment and remained disease active at 1- and 2-year follow-ups, indicating residual disease activity in BD. Patients with a BDCAF score of 0 had a longer inflammatory major organ event-free survival at 52 weeks than those with a score of 1 or higher (p=2.2 x 10-4). Clustering analysis revealed that patients who did not achieve remission despite treatment with tumor necrosis factor inhibitors had high serum inflammatory cytokine levels and incidences of inflammatory major organ events. Among the elevated cytokines, IL-6 was associated with inflammatory major organ events. Conclusion: This study suggests that treatment strategies targeting overall disease activity and monitoring residual serum IL-6 may help prevent inflammatory major organ events in BD.

Predicting Prostate Surgery Outcomes from Standard Clinical Assessments of Lower Urinary Tract Symptoms To Derive Prognostic Symptom and Flowmetry Criteria.

BACKGROUND: Assessment of male lower urinary tract symptoms (LUTS) needs to identify predictors of symptom outcomes when interventional treatment is planned. OBJECTIVE: To develop a novel prediction model for prostate surgery outcomes and validate it using a separate patient cohort and derive thresholds for key clinical parameters. DESIGN, SETTING, AND PARTICIPANTS: From the UPSTREAM trial of 820 men seeking treatment for LUTS, analysis of bladder diary (BD), International Prostate Symptom Score (IPSS), IPSS-quality of life, and uroflowmetry data was performed for 176 participants who underwent prostate surgery and provided complete data. For external validation, data from a retrospective database of surgery outcomes in a Japanese urology department (n = 227) were used. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Symptom improvement was defined as a reduction in total IPSS of ≥3 points. Multiple logistic regression, classification tree analysis, and random forest models were generated, including versions with and without BD data. RESULTS AND LIMITATIONS: Multiple logistic regression without BD data identified age (p = 0.029), total IPSS (p = 0.0016), and maximum flow rate (Qmax; p = 0.066) as predictors of outcomes, with area under the receiver operating characteristic curve (AUC) of 77.1%. Classification tree analysis without BD data gave thresholds of IPSS <16 and Qmax ≥13 ml/s (AUC 75.0%). The random forest model, which included all clinical parameters except BD data, had an AUC of 94.7%. Internal validation using the bootstrap method showed reasonable AUCs (69.6-85.8%). Analyses using BD data marginally improved the model fits. External validation gave comparable AUCs for logistic regression, classification tree analysis, and random forest models (all without BD; 70.9%, 67.3%, and 68.5%, respectively). Limitations include the significant number of men with incomplete baseline data and limited assessments in the external validation cohort. CONCLUSIONS: Outcomes of prostate surgery can be predicted preoperatively using age, total IPSS, and uroflowmetry data, with prognostic thresholds of 16 for IPSS and 13 ml/s for Qmax. PATIENT SUMMARY: This study identified key preoperative factors that can predict outcomes of prostate surgery for bothersome urinary symptoms, including which patients are at risk of a poor outcome.

Models to predict the surgical outcome of mini-ECIRS (endoscopic combined intrarenal surgery) for renal and/or ureteral stones.

To establish a safer and more efficient treatment strategy with mini-endoscopic combined intrarenal surgery (ECIRS), the present study aimed to develop models to predict the outcomes of mini-ECIRS in patients with renal and/or ureteral stones. We retrospectively analysed consecutive patients with renal and/or ureteral stones who underwent mini-ECIRS at three Japanese tertiary institutions. Final treatment outcome was evaluated by CT imaging at 1 month postoperatively and stone free (SF) was defined as completely no residual stone or residual stone fragments ≤ 2 mm. Three prognostic models (multiple logistic regression, classification tree analysis, and machine learning-based random forest) were developed to predict surgical outcomes using preoperative clinical factors. Clinical data from 1432 ECIRS were pooled from a database registered at three institutions, and 996 single sessions of mini-ECIRS were analysed in this study. The overall SF rate was 62.3%. The multiple logistic regression model consisted of stone burden (P < 0.001), number of involved calyces (P < 0.001), nephrostomy prior to mini-ECIRS (P = 0.091), and ECOG-PS (P = 0.110), wherein the area under the curve (AUC) was 70.7%. The classification tree analysis consisted of the number of involved calyces with an AUC of 61.7%. The random forest model showed that the top predictive variable was the number of calyces involved, with an AUC of 91.9%. Internal validation revealed that the AUCs for the multiple logistic regression model, classification tree analysis and random forest models were 70.4, 69.6 and 85.9%, respectively. The number of involved calyces, and a smaller stone burden implied a SF outcome. The machine learning-based model showed remarkably high accuracy and may be a promising tool for physicians and patients to obtain proper consent, avoid inefficient surgery, and decide preoperatively on the most efficient treatment strategies, including staged mini-ECIRS.

The net benefit for time-to-event outcome in oncology clinical trials with treatment switching.

BACKGROUND: The net benefit is an effect measure for any type of endpoint, including the time-to-event outcome, and can provide intuitive and clinically meaningful interpretation. It is defined as the probability of a randomly selected subject from the experimental arm surviving by at least a clinically relevant time longer than a randomly selected subject from the control arm. In oncology clinical trials, an intercurrent event such as treatment switching is common, which potentially causes informative censoring; nevertheless, conventional methods for the net benefit are not able to deal with it. In this study, we proposed a new estimator using the inverse probability of censoring weighting (IPCW) method and illustrated an oncology clinical trial with treatment switching (the SHIVA study) to apply the proposed method under the estimand framework. METHODS: The net benefit can be estimated using the survival functions of each treatment group. The proposed estimator was based on the survival functions estimated by the inverse probability of the censoring weighting method that can handle covariate-dependent censoring. The simulation study was undertaken to evaluate the operating characteristics of the proposed estimator under several scenarios; we varied the shapes of the survival curves, treatment effect, covariates effect on censoring, proportion of the censoring, threshold of the net benefit, and sample size. We also applied conventional methods (the scoring rules by Péron or Gehan) and the proposed method to the SHIVA study. RESULTS: Our simulation study showed that the proposed estimator provided less biased results under the covariate-dependent censoring than existing estimators. When applying the proposed method to the SHIVA study, we were able to estimate the net benefit by incorporating the information of the covariates with different estimand strategies to address the intercurrent event of the treatment switching. However, the estimates of the proposed method and those of the aforementioned conventional methods were similar under the hypothetical strategy. CONCLUSIONS: We proposed a new estimator of the net benefit that can include covariates to account for the possibly informative censoring. We also provided an illustrative analysis of the proposed method for the oncology clinical trial with treatment switching using the estimand framework. Our proposed new estimator is suitable for handling the intercurrent events that can potentially cause covariate-dependent censoring.

Tumor steatosis and glutamine synthetase expression in patients with advanced hepatocellular carcinoma receiving atezolizumab plus bevacizumab therapy.

AIM: The anti-programmed death-ligand 1 antibody atezolizumab and vascular endothelial growth factor-neutralizing antibody bevacizumab in combination (Atezo + Bev) have become the first-line therapy in advanced hepatocellular carcinoma (HCC). Distinct types of tumor immune microenvironment (TIME) and their associations with specific molecular subclasses and driver gene mutations have been identified in HCC; however, these insights are mainly based on surgically resected early-stage tumors. The current study aimed to reveal the biology and TIME of advanced HCC and their significance in predicting clinical outcomes of Atezo + Bev therapy. METHODS: Thirty-three patients with advanced HCC who were scheduled for treatment with Atezo + Bev therapy were included in this study. Pretreatment tumor biopsy, pre- and posttreatment diffusion-weighted magnetic resonance imaging (MRI) with nine b values (0-1500 s/mm2 ), and other clinicopathologic factors were analyzed. RESULTS: Compared with resectable HCC, advanced HCC was characterized by higher proliferative activity, a higher frequency of Wnt/ß-catenin-activated HCC, and lower lymphocytic infiltration. Prognostically, two metabolism-related factors, histopathologically determined tumor steatosis and/or glutamine synthetase (GS) expression, and MRI-determined tumor steatosis, were the most significant prognostic indicators for progression-free survival (PFS) and overall survival after Atezo + Bev therapy. Furthermore, changes in the pre- and posttreatment true diffusion coefficients on MRI, which might reflect changes in TIME after treatment, were significantly associated with better PFS. CONCLUSIONS: The biology and TIME of HCC were strikingly different in advanced HCC compared with those of surgically resected HCC. Two metabolism-related factors, pathologically determined tumor steatosis and/or GS expression, and MRI-determined tumor steatosis, were found to be the most significant prognostic indicators for Atezo + Bev therapy in advanced HCC.

Comparisons of Radiofrequency Ablation, Microwave Ablation, and Irreversible Electroporation by Using Propensity Score Analysis for Early Stage Hepatocellular Carcinoma.

BACKGROUND: Despite the diversity of thermal ablations, such as radiofrequency ablation (RFA) and microwave ablation (MWA), and non-thermal ablation, such as irreversible electroporation (IRE) cross-comparisons of multiple ablative modalities for hepatocellular carcinoma (HCC) treatment remain scarce. Thus, we investigated the therapeutic outcomes of different three ablation modalities in the treatment of early stage HCC. METHODS: A total of 322 consecutive patients with 366 HCCs (mean tumor size ± standard deviation: 1.7 ± 0.9 cm) who underwent RFA (n = 216, 59.0%), MWA (n = 91, 28.3%), or IRE (n = 15, 4.7%) were included. Local tumor progression (LTP) rates for LTP were compared among the three modalities. Propensity score-matched analysis was used to reduce selection bias. RESULTS: A significant difference in 2-year LTP rates between the IRE and RFA groups (IRE, 0.0% vs. RFA, 45.0%; p = 0.005) was found. There was no significant difference in 2-year LTP rates between the IRE and MWA groups (IRE, 0.0% vs. MWA, 25.0%; p = 0.103) as well as between the RFA and MWA groups (RFA, 18.2% vs. MWA, 20.6%; p = 0.586). CONCLUSION: IRE provides better local tumor control than RFA as a first-line therapeutic option for small perivascular HCC.

Impact of correlations between prioritized outcomes on the net benefit and its estimate by generalized pairwise comparisons.

Benefit-risk balance is gaining interest in clinical trials. For the comprehensive assessment of benefits and risks, generalized pairwise comparisons are increasingly used to estimate the net benefit based on multiple prioritized outcomes. Although previous research has demonstrated that the correlations between the outcomes impact the net benefit and its estimate, the direction and magnitude of this impact remain unclear. In this study, we investigated the impact of correlations between two binary or Gaussian variables on the true net benefit values via theoretical and numerical analyses. We also explored the impact of correlations between survival and categorical variables on the net benefit estimates based on four existing methods (Gehan, Péron, Gehan with correction, and Péron with correction) in the presence of right censoring via simulation and application to actual oncology clinical trial data. Our theoretical and numerical analyses revealed that the true net benefit values were impacted by the correlations in various directions depending on the outcome distributions. With binary endpoints, this direction was governed by a simple rule with a threshold of 50% for a favorable outcome. Our simulation showed that the net benefit estimates based on Gehan's or Péron's scoring rule could be substantially biased in the presence of right censoring, and that the direction and magnitude of this bias were associated with the outcome correlations. The recently proposed correction method greatly reduced this bias, even in the presence of strong outcome correlations. The impact of correlations should be carefully considered when interpreting the net benefit and its estimate.

Clinical trial design and analysis for comparing three treatments with intra-individual right- and left-hand data.

BACKGROUND: Chemotherapy-induced peripheral neuropathy can occur in the right and left hand. Studies on prevention treatments for chemotherapy-induced peripheral neuropathy have largely adopted either self-controlled designs or parallel designs to compare two preventive treatments. When three treatment options (two experimental treatments and a control treatment) are available, both designs can be extended. However, no clinical trials have adopted a self-controlled design to compare three prevention treatments for chemotherapy-induced peripheral neuropathy. The incomplete block crossover design for more than two treatments can be extended to compare three treatments in the self-controlled design. In simple extension, some of the participants receive two experimental treatments in both hands; however, it may be difficult to administer different experimental treatments in both hands for practical reasons, such as a concern for the different types of unexpected adverse events. This study proposes a design and analysis method appropriate for the situation where only one experimental treatment is provided to each participant. METHODS: We assume clinical trials to compare each of the two experimental treatments (E1 and E2) with the control treatment (C) and between two experimental treatments only when both experimental treatments are superior to the control treatment. We propose a self-controlled design, which equally randomizes to four arms to adjust for the dominant hand effect: Arm 1: E1 for right hand, C for left hand; Arm 2: C for right hand, E1 for left hand; Arm 3: E2 for right hand, C for left hand; and Arm 4: C for right hand, E2 for left hand. We compare operating characteristics of the proposed design with the three-arm parallel design in which the same treatment is performed in both hands by participants. We also assess three proposed analysis methods for comparisons between experimental treatments in the self-controlled design under several conditions of correlations between right and left hands using simulation studies. RESULTS: The simulation studies showed that the proposed design was more powerful than the three-arm parallel design when correlation was 0.3 or higher. For comparisons between experimental treatments, the methods based on the regression model, including the outcome of hands with C as a covariate, had the highest power under modest to high correlation among the analysis methods in the self-controlled design. CONCLUSION: The proposed design can improve the power for comparing between two experimental treatments and the control treatment. Our design is useful in situations where it is undesirable for participants to receive different experimental treatments in both hands for practical reasons.

Optimal dose escalation methods using deep reinforcement learning in phase I oncology trials.

In phase I trials of a novel anticancer drug, one of the most important objectives is to identify the maximum tolerated dose (MTD). To this end, a number of methods have been proposed and evaluated under various scenarios. However, the percentages of correct selection (PCS) of MTDs using previous methods are insufficient to determine the dose for late-phase trials. The purpose of this study is to construct an action rule for escalating or de-escalating the dose and continuing or stopping the trial to increase the PCS as much as possible. We show that deep reinforcement learning with an appropriately defined state, action, and reward can be used to construct such an action selection rule. The simulation study shows that the proposed method can improve the PCS compared with the 3 + 3 design, CRM, BLRM, BOIN, mTPI, and i3 + 3 methods.

Clinical Significance of SEC11A Expression in Patients With Locally Advanced Gastric Cancer.

BACKGROUND/AIM: SEC11A gene encodes the SPC18 protein, which has been implicated in tumour progression by inducing the secretion of various growth factors. We investigated the clinical significance of SEC11A expression in gastric cancer (GC) tissues in patients with locally advanced gastric cancer (LAGC) after curative resection. PATIENTS AND METHODS: We estimated SEC11A expression in cancer tissues from 253 pStage II/III GC patients who underwent curative resection using quantitative polymerase chain reaction (PCR) and investigated the relationship of SEC11A expression with clinicopathological factors and survival. RESULTS: SEC11A expression was significantly related to serosal invasion, lymph node metastasis, lymphatic invasion, and pathological stage. The high-SEC11A expression group had a significantly lower survival rate than the low group (5-year survival 52.3% vs. 75.9%; p<0.005). Furthermore, in multivariate analysis, high-SEC11A expression was an independent factor of poor survival (hazard ratio, 2.010; 95% confidence interval=1.303-3.100; p=0.002). CONCLUSION: SEC11A expression in cancer tissue may be a useful prognostic marker in patients with LAGC after curative resection.

Statistical methods and graphical displays of quality of life with survival outcomes in oncology clinical trials for supporting the estimand framework.

BACKGROUND: Although there are discussions regarding standards of the analysis of patient-reported outcomes and quality of life (QOL) in oncology clinical trials, that of QOL with death events is not within their scope. For example, ignoring death can lead to bias in the QOL analysis for patients with moderate or high mortality rates in the palliative care setting. This is discussed in the estimand framework but is controversial. Information loss by summary measures under the estimand framework may make it challenging for clinicians to interpret the QOL analysis results. This study illustrated the use of graphical displays in the framework. They can be helpful for discussions between clinicians and statisticians and decision-making by stakeholders. METHODS: We reviewed the time-to-deterioration analysis, prioritized composite outcome approach, semi-competing risk analysis, survivor analysis, linear mixed model for repeated measures, and principal stratification approach. We summarized attributes of estimands and graphs in the statistical analysis and evaluated them in various hypothetical randomized controlled trials. RESULTS: Graphs for each analysis method provide different information and impressions. In the time-to-deterioration analysis, it was not easy to interpret the difference in the curves as an effect on QOL. The prioritized composite outcome approach provided new insights for QOL considering death by defining better conditions based on the distinction of OS and QOL. The semi-competing risk analysis provided different insights compared with the time-to-deterioration analysis and prioritized composite outcome approach. Due to the missing assumption, graphs by the linear mixed model for repeated measures should be carefully interpreted, even for descriptive purposes. The principal stratification approach provided pure comparison, but the interpretation was difficult because the target population was unknown. CONCLUSIONS: Graphical displays can capture different aspects of treatment effects that should be described in the estimand framework.

Effects of perioperative eicosapentaenoic acid-enriched oral nutritional supplement on the long-term oncological outcomes after total gastrectomy for gastric cancer.

Basic and clinical reports have suggested that eicosapentaenoic acid (EPA) exhibits anti-tumor activity. The present study evaluated whether perioperative EPA could improve the survival of patients with localized gastric cancer as a key secondary endpoint of a randomized clinical study. The present study was designed as multicenter, open-label, superiority, randomized trial to confirm the preventive effect of EPA on body weight loss after total gastrectomy for gastric cancer. Eligible patients were randomized to either the standard-diet group (EPA-off group) or EPA-on group by a centralized dynamic method. An EPA-enriched supplement (ProSure®) was given to the EPA-on group in addition to their standard diet. This supplement included 600 kcal with 2.2 g/day of EPA. Among the 126 patients who were randomized, 123 patients (EPA-off group, n=60; EPA-on group, n=63) were examined in the survival analyses. All background factors were well balanced between the two groups. The 3-year and 5-year overall survival rates were 74.6 and 67.8%, respectively, in the EPA-off group, and 77.8 and 76.2% in the EPA-on group. There was no significant difference between the EPA-off and EPA-on groups (hazard ratio, 0.77; P=0.424). In the subgroup analysis, the hazard ratio was 0.39 in patients who received neoadjuvant chemotherapy and 0.57 in patients with nodal metastasis. In conclusion, a clear survival benefit of perioperative EPA was not observed in localized gastric cancer. The value of EPA should be further tested in a future study in patients with unfavorable advanced gastric cancer. Clinical trial number: UMIN000006380; date of registration, September 21, 2011.

Comparison of modified CEUS LI-RADS with sonazoid and CT/MRI LI-RADS for diagnosis of hepatocellular carcinoma.

AIM: To compare the diagnostic performance based on the modified CEUS Liver Imaging Reporting and Data System (LI-RADS), which includes Kupffer-phase findings as a major imaging feature, with that of CT and MRI (CT/MRI) LI-RADS for liver nodules in patients at high risk of HCC. METHODS: A total of 120 patients with 120 nodules were included in this retrospective study. The median size of the lesions was 20.0 mm (interquartile range, 14.0-30.8 mm). Of these lesions, 90.0% (108 of 120) were confirmed as HCCs, 6.7% (8 of 120) were intrahepatic cholangiocarcinomas, 1.7% (2 of 120) were metastases, and 1.7% (2 of 120) were dysplastic nodules. All nodules were diagnosed histopathologically. Each nodule was categorized according to the modified CEUS LI-RADS and CT/MRI LI-RADS version 2018. The diagnostic performance and inter-modality agreement of each criterion was compared. RESULTS: The inter-modality agreement for the modified CEUS LI-RADS and CT/MRI LI-RADS was slight agreement (kappa = 0.139, p = 0.015). The diagnostic accuracies of HCCs for the modified CEUS LR-5 and CT/MRI LR-5 were 70.0% (95% confidence interval [CI]: 61.0%, 78.0%) versus 70.8% (95% CI: 61.8%, 78.8%) (p = 0.876), respectively. The diagnostic accuracies of non-HCC malignancies for the modified CEUS LR-M and CT/MRI LR-M were 84.2% (95% CI: 76.4%, 90.2%) versus 96.7% (95% CI: 91.7%, 99.1%) (p = 0.002), respectively. CONCLUSIONS: The diagnostic performance for HCCs on the modified CEUS LR-5 and CT/MRI LR-5 are comparable. In contrast, CT/MRI LR-M has better diagnostic performance for non-HCC malignancy than that of the modified CEUS LR-M.

Experience of distance education for project-based learning in data science.

Data science plays an important role in many fields. Project-based learning is an effective teaching approach because students can learn data science practices based on real-world problems and real-world data. Because of a pandemic of COVID-19, we provided project-based learning as distance education (synchronic distance education). In this study, we explain how we developed and conducted it and provide survey results from students. The survey showed about 30% of the students found it difficult to communicate with each other and with teachers. However, it suggested that they could communicate to some extent even by remote group work. We found that, in remote communication, it is important to see the faces of all the students (and teachers) on the Zoom screen when they discuss using screen sharing. There remain some challenges such as timing to start talking and casual questions to teachers. Although some issues should be improved, distance education for project-based learning in data science can be implemented effectively. Supplementary Information: The online version contains supplementary material available at 10.1007/s42081-022-00154-2.

A Japanese Box Lunch Bento Comprising Functional Foods Reduce Oxidative Stress in Men: A Pilot Study.

The elder population has increased, introducing the profound medical and social challenge of maintaining health in aging seniors and the need for a medical approach to sustaining physical and mental health. The relationship between diseases and lifestyle-related factors such as diet and exercise are important. A health-conscious lifestyle improves one's health condition from a medical perspective, as indicated by new wellness monitoring using health devices and recent research into the efficacy of functional lunches incorporating utilitarian agricultural, forestry, and fishery products and foods. For a period of 3 months, and solely at lunchtime, 21 participants consumed the contents of a bento (Japanese box lunch), which incorporated functional (healthy) foods. A variety of factors were analyzed, including: weight, weight fluctuation rate, abdominal girth, triglycerides, total cholesterol value, and 8-OHdG (8-hydroxy-2'-deoxyguanosine). The bento comprising functional foods resulted in a reduction in both weight and abdominal girth without calorie restrictions. A reduction over time was observed in 8-OHdG, an oxidative stress marker, as compared to values prior to initiation of the study. Usage of a health device, exercise/dietary advice from a physician and nutritionist, and the availability of meals incorporating functional agricultural products might help prevent lifestyle disease and lead to improved health management.

Noninvasive Diagnosis of Hepatocellular Carcinoma on Sonazoid-Enhanced US: Value of the Kupffer Phase.

The aim of this study was to compare the diagnostic performance of Contrast-Enhanced US Liver Imaging Reporting and Data System (CEUS LI-RADS) version 2017, which includes portal- and late-phase washout as a major imaging feature, with that of modified CEUS LI-RADS, which includes Kupffer-phase findings as a major imaging feature. Participants at risk of hepatocellular carcinoma (HCC) with treatment-naïve hepatic lesions (≥1 cm) were recruited and underwent Sonazoid-enhanced US. Arterial phase hyperenhancement (APHE), washout time, and echogenicity in the Kupffer phase were evaluated using both criteria. The diagnostic performance of both criteria was analyzed using the McNemar test. The evaluation was performed on 102 participants with 102 lesions (HCCs (n = 52), non-HCC malignancies (n = 36), and benign (n = 14)). Among 52 HCCs, non-rim APHE was observed in 92.3% (48 of 52). By 5 min, 73.1% (38 of 52) of HCCs showed mild washout, while by 10 min or in the Kupffer phase, 90.4% (47 of 52) of HCCs showed hypoenhancement. The sensitivity (67.3%; 35 of 52; 95% CI: 52.9%, 79.7%) of modified CEUS LI-RADS criteria was higher than that of CEUS LI-RADS criteria (51.9%; 27 of 52; 95% CI: 37.6%, 66.0%) (p = 0.0047). In conclusion, non-rim APHE with hypoenhancement in the Kupffer phase on Sonazoid-enhanced US is a feasible criterion for diagnosing HCC.

Optimal adaptive allocation using deep reinforcement learning in a dose-response study.

Estimation of the dose-response curve for efficacy and subsequent selection of an appropriate dose in phase II trials are important processes in drug development. Various methods have been investigated to estimate dose-response curves. Generally, these methods are used with equal allocation of subjects for simplicity; nevertheless, they may not fully optimize performance metrics because of nonoptimal allocation. Optimal allocation methods, which include adaptive allocation methods, have been proposed to overcome the limitations of equal allocation. However, they rely on asymptotics, and thus sometimes cannot efficiently optimize the performance metric with the sample size in an actual clinical trial. The purpose of this study is to construct an adaptive allocation rule that directly optimizes a performance metric, such as power, accuracy of model selection, accuracy of the estimated target dose, or mean absolute error over the estimated dose-response curve. We demonstrate that deep reinforcement learning with an appropriately defined state and reward can be used to construct such an adaptive allocation rule. The simulation study shows that the proposed method can successfully improve the performance metric to be optimized when compared with the equal allocation, D-optimal, and TD-optimal methods. In particular, when the mean absolute error was set to the metric to be optimized, it is possible to construct a rule that is superior for many metrics.

Survival analysis of a prospective multicenter observational study on surgical palliation among patients with malignant bowel obstruction caused by peritoneal dissemination of gastric cancer.

BACKGROUND: Our previous report showed that surgical palliation maintained quality of life (QOL), improved solid food intake, and had an acceptable surgical safety among patients with malignant bowel obstruction (MBO) caused by advanced gastric cancer. This study performed a survival analysis stratified by the patients' QOL to elucidate its impact on survival. METHODS: Patients who underwent resection or bypass of the small intestine/colon or ileostomy/colostomy for bowel obstruction caused by peritoneal dissemination of gastric cancer were included. Validated instruments (EuroQoL-5 Dimensions) were used to assess QOL at baseline and 2 weeks, 1 month, and 3 months following surgical palliation. Postoperative improvement in oral intake was also evaluated using the Gastric Outlet Obstruction Scoring System (GOOSS). Univariate and multivariate survival analyses were performed using baseline characteristics and changes in QOL and GOOSS scores 2 weeks after surgery to determine prognostic factors. RESULTS: We enrolled 60 patients with a median survival time of 6.64 (95% CI 4.76-10.28) months. Patients who received postoperative chemotherapy and had lower baseline C-reactive protein (CRP) levels, higher baseline albumin levels, better baseline EuroQoL-5 Dimensions (EQ-5D) scores, and improved oral intake after palliative surgery exhibited significantly better survival. Multivariate analysis identified postoperative chemotherapy, lower baseline CRP levels, and improved oral intake as independent prognostic factors. CONCLUSIONS: The current study revealed that baseline QOL and postoperative QOL changes did not affect survival. Moreover, improved oral intake, lower baseline CRP levels, and postoperative chemotherapy were significant prognostic factors in patients who underwent palliative surgery for advanced gastric cancer with MBO.

Definitions and elements of endpoints in phase III randomized trials for the treatment of COVID-19: a cross-sectional analysis of trials registered in ClinicalTrials.gov.

BACKGROUND: There are several challenges in designing clinical trials for the treatment of novel infectious diseases, such as COVID-19. In particular, the definition of endpoints related to the severity, time frame, and clinical course remains unclear. Therefore, we conducted a cross-sectional analysis of phase III randomized trials for COVID-19 registered at ClinicalTrials.gov . METHODS: We collected the data from ClinicalTrials.gov on March 31, 2021, by specifying the following search conditions under Advanced Search: Condition or disease: (COVID-19) OR (SARS-CoV-2); Study type: Interventional Studies; Study Results: All Studies; Recruitment: Not yet recruiting, Recruiting, Enrolling by invitation, Active, Not recruiting, Suspended, Completed; Sex: All; and Phase: Phase 3. From the downloaded search results, we selected trials that met the following criteria: Primary Purpose: Treatment; Allocation: Randomized. We manually transcribed information not included in the downloaded file, such as Primary Outcome Measures, Secondary Outcome Measures, Time Frame, and Inclusion Criteria. In the analysis, we examined primary and secondary endpoints in trials with severe and non-severe patients, including the types of endpoints, time frame, clinical course, and sample size. RESULTS: A total of 406 trials were included in the analysis. The median numbers of endpoints in trials with severe and non-severe patients were 9 and 7, respectively. Approximately 25% of the trials used multiple primary endpoints. Regardless of the type of endpoint, the time frames were longer in the trials with severe patients than in the trials with non-severe patients. In the evaluation of the clinical course, worsening was often considered in binary endpoints, and improvement was considered in time-to-event endpoints. The sample size was the largest in clinical trials using binary endpoints. CONCLUSIONS: Endpoints can differ with respect to severity, and the clinical course and time frame are important for defining endpoints. This study provides information that can facilitate the achievement of a consensus for the endpoints in evaluating COVID-19 treatments.