A retrospective cohort study of tamoxifen versus surgical treatment for ER-positive gynecomastia.

BACKGROUND: Gynecomastia is a common condition in clinical practice. The present study aimed to review the clinical data of ER-positive gynecomastia patients treated by tamoxifen (TAM) versus surgery and discussed the clinical effects of the two treatment strategies. METHOD: We retrospectively collected the clinical indicators of patients with unilateral or bilateral gynecomastia who received treatment at our hospital between April 2018 and December 2021. Depending on the treatment received, the patients were divided into TAM and surgery groups. RESULT: A total of 170 patients were recruited, including 91 patients in TAM group and 79 patients in surgery group. The age of the patients differed significantly between the TAM and surgery groups (P < 0.01). The estrogen level was closer in patients with stable and progressive disease, but significantly different in patients of glandular shrinkage in TAM group (P < 0.01). The proportion of patients achieving stable disease was higher among those with clinical grade 1-2. Among patients classified as clinical grade 3, the proportion of patients achieving glandular shrinkage of the breast was higher after TAM treatment (P < 0.05). The age and length of hospital stay were significantly different in patients undergoing open surgery than minimally invasive rotary cutting surgery and mammoscopic-assisted glandular resection (P < 0.01). Patients had significantly different complications including mild postoperative pain, hematoma, nipple necrosis, nipple paresthesias and effusions among the surgery subgroups (all P < 0.05). The estrogen level and the type of surgery were significantly different between the surgical recurrence and non-recurrence subgroups (P < 0.05). The difference in the thickness of glandular tissues upon the color Doppler ultrasound also reached a statistical significance between the two groups (P = 0.050). An elevated estrogen level was a factor leading to TAM failure. Among surgical patients, the thickness of glandular tissues, estrogen level, and type of surgery performed were risk factors for postoperative recurrence (all P < 0.05). CONCLUSION: Both treatment strategies can effectively treat gynecomastia, but different treatment methods can benefit different patients. TAM treatment is more beneficial than surgery for patients who cannot tolerate surgery, have a low estrogen level, and are clinical grade 1-2. Surgery treatment is better than TAM for patients of clinical grade 3. Different surgery options may lead to different complications. Patients with a greater glandular tissue thickness and a higher estrogen level were shown to have a higher risk of recurrence.

Practical considerations in utilizing cluster randomized controlled trials conducted in biopharmaceutical industry.

Cluster randomized controlled trials (cluster RCTs), also known as parallel-arm group-randomized trials, are trials in which the randomized units are groups of participants, as opposed to individual participants. These trials have largely been implemented to address broad public health issues, but with the growing interest in use of real-world data in the regulatory setting, this design may be increasingly considered for industry trials. The key difference between cluster RCTs and traditional RCTs is the intraclass correlation coefficient (ICC) that needs to be considered in cluster RCTs. In this article, we discuss some key practical considerations that are related to ICC in the design, conduct, analysis, and report stages of a cluster RCT. These key considerations related to ICC can lead to improvement in how we translate research findings from cluster RCTs into practices in the biopharmaceutical industry.

A comparative study of the efficacy of tamoxifen and Chinese patented medicine (Pingxiao capsules) in gynecomastia: A retrospective cohort study.

To compare the clinical efficacy of tamoxifen and Chinese patented medicine (Pingxiao capsules) in patients with gynecomastia and discuss the safety of the two treatments. We retrospectively analysed the clinical data of 388 male patients with gynecomastia who were treated in the Outpatient Clinic of our hospital between January 2010 and December 2020. There were 103 patients in the tamoxifen (TAM) group and 103 patients in the Chinese patented medicine group. There were 182 patients in the observation group (non-medication group; age range, 11-75 years; average age, 33.1 years). The natural outcomes were compared between the observation and two medication groups under the same conditions. Disease progression was compared between the observation and two medication groups over the same treatment duration to confirm the efficacy of the medication treatments. Patients with clinical grade 2 gynecomastia accounted for the highest proportion of patients in the TAM group. The percentage of patients with clinical grade 2 gynecomastia was comparable in the Chinese patented medicine and observation groups. The percentage of patients with clinical grades 1 and 3 gynecomastia was the lowest in the TAM group and comparable among the three groups (p = 0.014). The TAM group had the largest number of patients achieving breast shrinkage, and therefore had the best efficacy (p = 0.000). Among the three groups, the surgery rate was the highest in the observation group (p = 0.000). Patients with the greatest glandular tissue thickness achieved better outcomes after medication treatment (p = 0.000). Patients with a higher clinical grade also had a higher surgery rate (p = 0.000). Some patients from the TAM and Chinese patented medicine groups had side effects. TAM results in better outcomes than Chinese patented medicine in gynecomastia patients. The surgery rate is the highest in the observation group. In addition, among some patients with a greater glandular tissue thickness, the higher the clinical grade is, the higher the surgery rate is. Both TAM and Chinese patented medicine cause some side effects and should be used with caution along with continuous follow-up evaluation of patients receiving either treatment.

Smartphone-Based and Data-Driven Superstructure State Prediction Method for Highway Bridges in Service.

Survival analysis is a data-driven approach that is widely used in various fields of biomedical prognostic research, and it is highly reliable in the processing of time-event data. This study developed a method for evaluating the service performance of bridge superstructures using the built-in acceleration sensor of smartphones and the prediction of survival analysis theory. It will be used to assist in the daily maintenance and repair of small and medium bridges. The effects of the upper load-bearing structure, upper general structure, bearings, deck paving, expansion joints, and frequency ratio on the deterioration of the bridge superstructure were investigated. The results show that the first-order vibration frequency of the bridge can be effectively detected by the built-in acceleration sensor of the mobile phone, but its low sensitivity and high output noise make it impossible to accurately detect the higher-order frequencies of the bridge. The upper load-bearing members, the upper general structure, the bearing, the deck pavement, and the frequency ratio are all related to the changing trend of the technical condition level of the bridge superstructure.

Presenting Risks and Benefits: Helping the Data Monitoring Committee Do Its Job.

Data monitoring committees (DMCs), or data and safety monitoring boards, protect clinical trial participants by conducting benefit-risk assessments during the course of a clinical trial. These evaluations may be improved by broader access to data and more effective analyses and presentation. Data monitoring committees should have access to all data, including efficacy data, at each interim review. The DMC reports should include graphical presentations that summarize benefits and harms in efficient ways. Benefit-risk assessments should include summaries that are consistent with the intention-to-treat principle and have a pragmatic focus. This article provides examples of graphical summaries that integrate benefits and harms, and proposes that such summaries become standard in DMC reports.

A method for sample size calculation via E-value in the planning of observational studies.

Confounding adjustment plays a key role in designing observational studies such as cross-sectional studies, case-control studies, and cohort studies. In this article, we propose a simple method for sample size calculation in observational research in the presence of confounding. The method is motivated by the notion of E-value, using some bounding factor to quantify the impact of confounders on the effect size. The method can be applied to calculate the needed sample size in observational research when the outcome variable is binary, continuous, or time-to-event. The method can be implemented straightforwardly using existing commercial software such as the PASS software. We demonstrate the performance of the proposed method through numerical examples, simulation studies, and a real application, which show that the proposed method is conservative in providing a slightly bigger sample size than what it needs to achieve a given power.

The Vacuum-Assisted Breast Biopsy System is an Effective Strategy for the Treatment of Gynecomastia.

BACKGROUND: Gynecomastia is the most common benign disease in males with an increasing prevalence in recent years. It may cause local pain and psychological disorders. The vacuum-assisted breast biopsy system has been reported to be a novel surgical approach for the treatment of gynecomastia. However, there are little detailed reports comparing the curative effect between traditional surgery and vacuum-assisted breast biopsy for gynecomastia. Besides, there was little study which compared the application of two different systems for the treatment of gynecomastia. Our study aimed to investigate the effectiveness of vacuum-assisted breast biopsy systems for patients with gynecomastia. METHODS: We retrospectively reviewed 83 patients with gynecomastia between January 2015 and December 2019. Open surgery was performed in 56 patients, and vacuum-assisted breast biopsy was performed in 27 patients. The characteristics of patients as well as the curative effects between the two groups were analyzed. The two vacuum-assisted breast biopsy systems (Mammotome and Encor) were performed for the patients with gynecomastia. The efficacy, safety, complications, and patient satisfactions were recorded during postoperative follow-up periods. RESULTS: Compared with the open surgery group, the vacuum-assisted breast biopsy group had significantly smaller scar sizes left after the operation (5.5 ± 1.3 cm vs 0.8 ± 0.2 cm, p < 0.001), and shorter hospital stay time (5.5 ± 2.4 ds vs 3.1 ± 1.6 ds, p < 0.001). Patients in vacuum-assisted breast biopsy group had a better cosmetic outcome than those in open surgery group. There were no statistically significant differences between the two vacuum-assisted breast biopsy systems according to the mean age, the mean operation time, sites, or grade. In addition, no serious complications were observed in vacuum-assisted breast biopsy group. All the patients recovered well and were satisfied with the cosmetic outcomes. CONCLUSION: The vacuum-assisted breast biopsy system can be used as a feasible and minimally invasive approach for the treatment of gynecomastia. LEVEL OF EVIDENCE IV: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Intraspinal administration of interleukin-7 promotes neuronal apoptosis and limits functional recovery through JAK/STAT5 pathway following spinal cord injury.

It has been previously reported that the blockade of interleukin-7 receptor (IL-7R) promotes functional recovery following spinal cord injury (SCI), however, the direct function and molecular mechanism of IL-7 involved in this pathogenic process are unclear. Here, we report that, contrary to IL-7R blockade, the intraspinal administration of IL-7 limits functional recovery following SCI. In addition, IL-7 treatment promotes neuronal apoptosis in spinal cord lesions, which may be attributed to exacerbated focal inflammatory response, as shown by increased accumulation of activated microglia/macrophage and production of proinflammatory mediators. Moreover, IL-7 treatment activates JAK/STAT5 pathway following SCI. At last, more importantly, the pharmacological inhibition of STAT5 abrogates the effects of IL-7 treatment on functional recovery, neuronal apoptosis and focal inflammatory response, suggesting that the effects of IL-7 treatment following SCI are dependent on activating the JAK/STAT5 pathway. Overall, this study reveals the JAK/STAT5 pathway-dependent detrimental role of IL-7 following SCI, and also implies that targeting the IL-7/JAK/STAT5 axis may represent a potential therapeutic approach for SCI treatment.

Erianin serves as an NFATc1 inhibitor to prevent breast cancer-induced osteoclastogenesis and bone destruction.

INTRODUCTION: Breast cancer-related bone metastasis can lead to skeletal-related events (SREs), which decrease patient quality of life. Inhibition of osteoclastogenesis is a key treatment for SREs; however, the availability of clinical drugs remains limited, and all existing ones disrupt physiological bone formation, while exhibiting no effect on patient survival time. OBJECTIVES: This study aimed to identify a novel osteoclast inhibitor for the treatment of breast cancer-induced SREs. METHODS: The MDA-MB-231 breast cancer cell-induced bone loss model was used to investigate the therapeutic effects of erianin in vivo. Then, we evaluated the inhibitory effects of erianin on osteoclastogenesis and signalling in bone marrow-derived macrophages (BMMs) induced by conditioned medium from MDA-MB-231 breast cancer cells (231 CM) and receptor activator of nuclear factor-κB ligand (RANKL) in vitro. Next, a Cellular Thermal Shift Assay and siRNA-mediate knockdown were performed, to investigate the target of erianin during osteoclast formation. The effects of erianin on human osteoclastogenesis were evaluated using CD14+ monocytes obtained from patients with breast cancer. RESULTS: Erianin effectively improved breast cancer cells-induced bone destruction at doses of 2 and 20 mg/kg/day in vivo, while suppressing osteoclastogenesis and the upregulation of SRC-NFATc1, INTEGRIN ß3-MMP9 signals induced by 231 CM and RANKL in vitro. Furthermore, erianin interacted with NFATc1 but not SRC, and Nfatc1 knockdown eliminated the inhibitory effects of erianin on osteoclastogenesis. Notably, lower expression of NFATc1 positively correlated with longer survival in patients with cancer and a high risk of bone metastasis. We further revealed that 62.5-250 nM erianin suppresses NFATc1 and excessive osteoclastogenesis in CD14+ monocytes from patients with breast cancer. CONCLUSION: Erianin acts as an NFATc1 inhibitor that attenuates breast cancer-induced osteoclastogenesis and bone destruction.

A Flexible Ensemble Learning Method for Survival Extrapolation.

OBJECTIVES: Survival extrapolation is an important statistical concept for estimating long-term survival from short-term clinical trial data. It is widely used in health technology assessment (HTA). Survival extrapolation is often performed by fitting one or two parametric models selected based on experience or selecting a model based on some goodness of fit statistics from a predefined collection of models. The main challenge in survival extrapolation is that the result is sensitive to model misspecification. In this study, we aim to propose a new approach that has a robust performance for survival extrapolation. METHODS: We propose a new method called Ensemble Learning for Survival Extrapolation (ELSE). Instead of selecting one best model from a predefined collection, ELSE builds an ensemble model based on a collection of models from the model library. Under this framework, we construct a point estimate of the long-term survival with a weighted average of the estimates of all candidate models and derive confidence intervals using nonparametric bootstrap. RESULTS: With our extensive numerical simulation studies, the proposed ELSE method shows better performance than the traditionally used model selection procedure based on Akaike Information Criterion (AIC). With a real data application to the Therapeutically Applicable Research to Generate Effective Treatment Wilms Tumor project (TARGET-WT) data, the ELSE method produces better survival extrapolation results in point estimate accuracy and confidence interval coverage. CONCLUSIONS: We developed an ensemble learning method for survival extrapolation (ELSE) which is robust for the underline data model and has good real data performance.

A framework for joint modeling and joint assessment of efficacy and safety endpoints for probability of success evaluation and optimal dose selection.

The evaluation of clinical proof of concept, optimal dose selection, and phase III probability of success has traditionally been conducted by a subjective and qualitative assessment of the efficacy and safety data. This, in part, was responsible for the numerous failed phase III programs in the past. The need to utilize more quantitative approaches to assess efficacy and safety profiles has never been greater. In this paper, we propose a framework that incorporates efficacy and safety data simultaneously for the joint evaluation of clinical proof of concept, optimal dose selection, and phase III probability of success. Simulation studies were conducted to evaluate the properties of our proposed methods. The proposed approach was applied to two real clinical studies. On the basis of the true outcome of the two clinical studies, the assessment based on our proposed approach suggested a reasonable path forward for both clinical programs.

Differential expression profile of mRNAs, lncRNAs, and circRNAs reveals potential molecular mechanism in breast cancer.

In recent years, breast cancer attracts more and more attention because of its high incidence. To explore the molecular functions and mechanisms, we performed RNA sequencing on the tumor tissues and their paired normal tissues from three breast cancer patients. By differential expression analysis, we found 3764 differentially expressed (DE) mRNAs, 5416 DE lncRNAs, and 148 DE circRNAs. Enrichment analysis suggested that the DE lncRNAs and DE circRNAs were enriched in mitochondria and nucleus, which indicated that they may participate in the vital metabolism directly or indirectly, such as fatty acid metabolism. Subsequently, the protein-protein interaction (PPI) network was constructed and we got 8 key proteins, of which the matrix metalloproteinase-9 (MMP9; degree 5) draws our attention. Based on the 38 up-regulated circRNAs and 14 down-regulated circRNAs, we constructed competing endogenous RNA (ceRNA) networks, from which the has-miR-6794-5p has been identified to enriched in the up-regulated network and correlated with the circNFIX directly. At this point, we presented that the circNFIX and MMP9 may play a significant role by regulating fatty acid metabolism in breast cancer.

Tirofiban combined with heparin's effect and safety in the treatment of mild to moderate acute ischemic stroke.

Tirofiban can be used to treat patients with acute ischemic stroke (AIS), this study was to evaluate the efficacy and safety of tirofiban combined with heparin in the treatment of mild to moderate AIS. A total of 98 patients with mild to moderate AIS randomly were divided into 2 groups within 48 h: the treatment group treated with tirofiban and, and the control group treated with aspirin + clopidogrel. The treatment group was given the same scheme as the control group after the treatment of tirofiban combined with heparin for 48 h. It was found that, compared with the control group, a significant decreased National Institute of Health stroke scale (NIHSS) was found in 48 h and 14 d, especially to the Barthel index (BI) in the treatment group (P < 0.05). Furthermore, Modified Rankin Scale (MRS, ≤2) in the treatment group was significantly upregulated in 90 d (P < 0.05). However, there were no significant differences in the adverse drug reactions between the two groups. It was indicated that nerve function and long-term prognosis in patients undergoing heparin for mild to moderate AIS were obviously improved than the control group.

Key considerations in the design of real-world studies.

Randomized controlled clinical trials (RCTs) are the gold standard for evaluating the safety and efficacy of pharmaceutical drugs, but in many cases their costs, duration, limited generalizability, and ethical or technical feasibility have caused some to look for real-world studies as alternatives. However, real-world studies may be less convincing due to the lack of randomization and blinding. In this article, we discuss some key considerations in the design of real-world studies, which include experimental studies (e.g., hybrid or pragmatic clinical trials and non-randomized single-arm clinical trials with external controls) and non-experimental studies (e.g., cohort studies, cross-sectional studies, and case-control studies). Causal inference plays a critical role in the derivation of robust real-world evidence (RWE) from the analysis of real-world data (RWD). Therefore, we apply the hypothetical strategy, along with the concept of potential outcome, to lay out these key considerations, and we hope these considerations are helpful for the design, conduct, and analysis of real-world studies.

A new framework to address challenges in quantitative benefit-risk assessment for medical products.

In recent years, there has been a proliferation of regulatory and industry-wide initiatives on structured benefit-risk (BR) assessment. Examples of structured BR frameworks include the PrOACT-URL (Problem formulation, Objectives, Alternatives, Consequences, Trade-Offs, Uncertainties, Risk Attitude and Linked Decisions) from European Medicines Agency Work Package 3, multiple U.S. Food and Drug Administration guidance documents on benefit-risk assessment for medical devices, and U.S. Food and Drug Administration implementation plans for benefit-risk assessment in drug regulatory decision-making. In June 2016, the ICH Expert Working Group finalized the Common Technical Document (CTD) Section 2.5.6 on Benefit-Risk Evaluations. As a result of these efforts, the uptake and utilization of structured benefit-risk (BR) assessments has been increasing. However, the aforementioned BR frameworks are mostly qualitative in nature, and the utility of quantitative BR approaches has not been systemically explored, creating uncertainty about settings in which quantitative BR assessment (qBRA) could be optimally applied. In this paper, we will provide an overview of the current qBRA methods, discuss challenges of qBRA, and describe a structural qBRA framework. The performance of the described qBRA framework will be evaluated by simulations based on a case study.

A Statistical Roadmap for Journey from Real-World Data to Real-World Evidence.

Randomized controlled clinical trials are the gold standard for evaluating the safety and efficacy of pharmaceutical drugs, but in many cases their costs, duration, limited generalizability, and ethical or technical feasibility have caused some to look for real-world studies as alternatives. On the other hand, real-world data may be much less convincing due to the lack of randomization and the presence of confounding bias. In this article, we propose a statistical roadmap to translate real-world data (RWD) to robust real-world evidence (RWE). The Food and Drug Administration (FDA) is working on guidelines, with a target to release a draft by 2021, to harmonize RWD applications and monitor the safety and effectiveness of pharmaceutical drugs using RWE. The proposed roadmap aligns with the newly released framework for FDA's RWE Program in December 2018 and we hope this statistical roadmap is useful for statisticians who are eager to embark on their journeys in the real-world research.

On a Stepwise Quantitative Approach for Benefit-Risk Assessment.

The field of structured benefit-risk assessment has evolved rapidly in the last few years with a great deal of regulatory and industry-wide initiatives. The available structured approaches to benefit-risk assessments exhibit and share many common elements in terms of defining the decision problem and therapeutic context, identifying key benefit and risk factors, and interpreting and communicating benefit-risk findings. However, there is limited guidance with these initiatives that is specific to metrics and methods to conduct benefit-risk assessment. Although we agree that benefit-risk metrics and analysis methods may be specific to individual clinical settings, we believe that there are general principles that can be followed. In this article, we propose a stepwise quantitative approach for benefit-risk assessment. We applied the stepwise quantitative approach to 3 real case studies.

The Case for a Bayesian Approach to Benefit-Risk Assessment:: Overview and Future Directions.

The benefit-risk assessment of a new medicinal product or intervention is one of the most complex tasks that sponsors, regulators, payers, physicians, and patients face. Therefore, communicating the trade-off of benefits and risks in a clear and transparent manner, using all available evidence, is critical to ensure that the best decisions are made. Several quantitative methods have been proposed in recent years that try to provide insight into this challenging problem. Bayesian inference, with its coherent approach for integrating different sources of information and uncertainty, along with its links to optimal decision theory, provides a natural framework to perform quantitative assessments of the benefit-risk trade-off. This paper describes the current state of the art in Bayesian methodologies for quantitative benefit-risk assessment, and how these may be leveraged throughout the life cycle of a medicinal product to support and augment clinical judgment and qualitative benefit-risk assessments. Gaps and potential new directions that extend the current approaches are also identified.

Addressing Challenges and Opportunities of "Less Well-Understood" Adaptive Designs.

The draft adaptive design guidance released by FDA in 2010 included references to adaptive study designs that were described as "less well-understood." At that time, there was relatively little regulatory experience with such designs, and their properties were felt to be insufficiently understood. In order to promote greater use of adaptive designs, especially those categorized as less well-understood, the Best Practice Subteam of the DIA Adaptive Designs Scientific Working Group (ADSWG) has worked on describing and characterizing these designs, identifying challenges associated with them and suggesting improvements to design or study conduct aspects that might make them more acceptable. This paper summarizes the work from the subteam.

DIA's Adaptive Design Scientific Working Group (ADSWG): Best Practices Case Studies for "Less Well-understood" Adaptive Designs.

Adaptive design (AD) clinical trials use accumulating subject data to modify the parameters of the design of an ongoing study, without compromising the validity and integrity of the study. The 2010 US Food and Drug Administration (FDA) Draft Guidance on Adaptive Design Clinical Trials described a subset of 7 primary design types as "less well-understood." FDA defined these designs as those with limited regulatory experience. To better understand the properties of these less well-understood ADs and to promote their use when applicable, the Best Practices Subteam for DIA's Adaptive Design Scientific Working Group conducted an extensive nonsystematic search and reviewed trials from multiple sponsors who had employed these designs. Here, we review 10 specific case studies for which less well-understood ADs were employed and share feedback about their challenges and successes, as well as details about the regulatory interactions from these trials. We learned that these designs and associated statistical methodologies can make difficult research situations more amenable for study and, therefore, are needed in our toolbox. While they can be used to study many diseases, they are particularly valuable for rare diseases, small populations, studies involving terminal illnesses, and vaccine trials, in which it is important to find efficient ways to bring effective treatments to market more rapidly. It is imperative, however, that these methodologies be utilized appropriately, which requires careful planning and precise operational execution.