Real-world Data Research Articles

Clinical outcomes of adjuvant nivolumab in resected stage III melanoma: comparison of CheckMate 238 trial and real-world data.

Nivolumab is approved as adjuvant therapy for resected stage III/IV melanoma based on the phase 3 CheckMate 238 trial. This analysis compared outcomes from CheckMate 238 with those from the real-world Flatiron Health electronic health record-derived de-identified database in patients with resected stage III melanoma (per AJCC-8) treated with adjuvant nivolumab. Outcomes included baseline characteristics, overall survival (OS) in the CheckMate 238 cohort (randomization until death or last known alive), and real-world overall survival (rwOS) in the Flatiron Health cohort (nivolumab initiation until death or data cutoff). rwOS was compared with OS using unadjusted and adjusted Cox proportional hazards models. Inverse probability of treatment weighting (IPTW) was combined with the adjusted model to reduce baseline discrepancies. The CheckMate 238 and real-world cohorts included 369 and 452 patients, respectively (median age, 56.0 and 63.0years; median follow-up, 61.4 vs. 25.5months). rwOS was not different from OS in the unadjusted (hazard ratio [HR] 1.27; 95% CI 0.92-1.74), adjusted (HR 1.01; 95% CI 0.67-1.54), and adjusted IPTW (HR 1.07; 95% CI 0.70-1.63) analyses. In the adjusted analysis, 2-year OS and rwOS rates were 84%. Median OS and rwOS were not reached. After IPTW, OS and rwOS were not different (HR 1.07; 95% CI 0.70-1.64). In this comparative analysis, OS in the CheckMate 238 trial was similar to rwOS in the Flatiron Health database after adjustments in patients with resected stage III melanoma (per AJCC-8) treated with adjuvant nivolumab, validating the trial results.

Patient-reported outcomes of topical finasteride/minoxidil treatment for male androgenetic alopecia: A retrospective study using telemedical data.

Oral finasteride and topical minoxidil are the current standard of care for male androgenetic alopecia and a combination of the two treatments can be considered for greater efficacy. Clinical trials of topical finasteride have also yielded promising results, but routine care data are lacking. To examine patient-reported outcomes of men with androgenetic alopecia who received topical finasteride admixed with minoxidil compared to the current standard of care (oral finasteride). Retrospective, cross-sectional study with data from a German direct-to-consumer teledermatology platform between December 2021 and January 2023. Patient-reported outcomes were collected through voluntary follow-up questionnaires provided after 6 weeks on topical finasteride/minoxidil or oral finasteride treatment. A total of 1545 patients who received topical finasteride/minoxidil treatment were included; 238 (15.4%) participated in the follow-up questionnaire. At week six, 62.2% (148/238) reported positive changes in their hair appearance, and 44.1% (105/238) reported an improvement of self-esteem. Treatment-related adverse events were reported in 11.8% (28/238). Full treatment adherence was observed in 74.4% (177/238). Comparing the topical treatment group to those receiving oral finasteride, lower treatment adherence was reported, along with higher rates of local adverse events; no difference was found in the incidence of sexual adverse events. Based on patient-reported outcomes, topical finasteride/minoxidil seems to be effective and well tolerated, but not superior to oral finasteride. Lower treatment adherence for topical usage must be considered when considering treatment options. Additional real-world data are needed to further evaluate the efficacy and safety of topical finasteride/minoxidil.

A Retrospective Budget Impact Analysis of Fidaxomicin Treatment for Clostridioides difficile Infections (CDI) in Germany.

Clostridioides difficile is the most common cause of healthcare-associated diarrhea. Research suggests that treating C. difficile infections (CDI) with fidaxomicin (FDX) is more effective than vancomycin (VAN), with potential cost savings. The objective was to calculate the budget impact of FDX treatment compared to VAN from a German payer perspective. The analysis used real-world data of patients discharged from University Hospital Cologne between Jan-01-2018 and Dec-31-2019. We identified recurrent and non-recurrent CDI cases and calculated direct treatment costs based on G-DRG flat rates. To calculate average costs per treatment and the budget impact, recurrence probabilities for VAN and FDX were taken from published evidence (28-day and 90-day scenarios). Totally, 475 cases were analyzed, thereof 421 non-recurrent, causing mean costs of €32,901 per case (95% CI: 27.752-38.050). Thirty-two patients experienced a recurrence within 28 days, yielding mean costs of €10,952 (95% CI: 5.627-16.277) for their additional hospital stay. The resulting budget impact was €1,303 (95% CI: 670 - 1.937) in favor of FDX, ranging from €148.34 to €2,190.30 in scenario analyses. The analysis indicates FDX treatment can lead to cost savings compared to VAN. Future research should focus on specific patient groups, such as refractory CDI patients.

Number of positive lymph nodes and lymph node ratio predict recurrence and survival in hypopharyngeal cancer based on SEER database and validation of real-world data.

This study investigated the impacts of the number of positive lymph nodes (NPLN) and lymph node ratio (LN ratio) for patients with hypopharyngeal squamous cell carcinoma (HPSCC) based on SEER database, which were validated in the real-world data of China. A total of 520 patients from SEER database were analyzed. Then 195 patients with pathologically stage III or IV HPSCC in our center were retrospectively studied. In the SEER database, NPLN ≥ 3 was found in 36.9% of patients. Multivariate analysis revealed that LN ratio ≥ 0.138 was significant with poorer overall survival (OS) (hazard ratio [HR] = 1.525, p = 0.001) and cancer-specific survival (CSS) (HR = 1.697, p < 0.001), so was the NPLN ≥ 3 (HR = 1.388, p = 0.013; HR = 1.479, p = 0.008). Patients with NPLN ≥ 3 were found in 103 (52.8%) in our center. Multivariate analysis confirmed a significant association regarding OS (p = 0.005) or CSS (p = 0.003) between patients with LN ratio ≥ 0.138 or not. In addition, disease recurrence rate differed significantly between the patients with NPLN ≥ 3 (27.2%) and NPLN < 3 (14.1%, p = 0.026). Moreover, postoperative chemoradiotherapy (CCRT) was significantly associated with better prognosis in patients with NPLN ≥ 3. In the SEER database, NPLN ≥ 3 and LN ratio ≥ 0.138 were independent poor prognostic factors for patients with HPSCC. Whereas identifying worldwide cut-off values for LN ratio is difficult and surgeon-dependent. In our cohort, adjuvant CCRT was beneficial for OS in patients with NPLN ≥ 3.

Comparative effectiveness of sodium-glucose cotransporter-2 inhibitors and dipeptidyl peptidase-4 inhibitors in improvement of fatty liver index in patients with type 2 diabetes mellitus and metabolic dysfunction-associated steatotic liver disease: A retrospective nationwide claims database study in Japan.

To date, there are limited clinical studies and real-world evidence investigating whether sodium-glucose cotransporter-2 inhibitors (SGLT2i) are associated with improved hepatic steatosis. This study aimed to evaluate the effectiveness of SGLT2i compared with that of dipeptidyl peptidase-4 inhibitors (DPP4i) in improving the fatty liver index (FLI) in patients with type 2 diabetes mellitus (T2DM) and metabolic dysfunction-associated steatotic liver disease (MASLD). This retrospective cohort study included new users of SGLT2i or DPP4i with T2DM and MASLD from a large claims database (JMDC Claims Database). The primary outcome was the incidence of improvement of the FLI. Cox proportional hazard models, weighted using propensity scores for predicting the initiation of treatment, were fitted to estimate hazard ratios with 95% confidence intervals (CIs). Time-course changes in the FLI values were also assessed. This study included 9127 SGLT2i and 12 286 DPP4i initiators. SGLT2i showed a higher incidence of improvement in the FLI (≥30%, ≥40% and ≥50% reduction from baseline FLI) compared with DPP4i, and the weighted hazard ratios were 1.27 (95% CI 1.18-1.38), 1.24 (95% CI 1.13-1.37) and 1.19 (95% CI 1.05-1.33), respectively. SGLT2i indicated a greater decreased in FLI values compared with DPP4i at up to 3 years of the follow-up period. SGLT2is use appeared to be associated with a greater improvement of the FLI than DPP4i use in patients with T2DM and MASLD. In the absence of direct head-to-head comparisons from clinical studies, our study, using real-world data, may support physicians' decision-making in clinical practice.

Sleeping more than 8 h: a silent factor contributing to decreased muscle mass in Chinese community-dwelling older adults

BackgroundMuscle mass loss is an age-related process that can be exacerbated by lifestyle, environmental and other factors, but can be mitigated by good sleep. The objective of this study was to investigate the correlation between varying time lags of sleep duration and the decline in muscle mass among individuals aged 60 years or older by using real-world health monitoring data obtained from wearable devices and smart home health monitoring devices.MethodsThis study included 86,037 observations from 2,869 participants in the Mobile Support System database. Missing data were supplemented by multiple imputation. The investigation utilized generalized estimating equations and restricted cubic spline curve to examine the relationship between sleep duration and low muscle mass. Various lag structures, including 0, 1, 2, 0–1, 0–2, and 1–2 months, were fitted, and the interaction effect of observation time with sleep duration was estimated for each lag structure. Additionally, subgroup analyses were conducted. The models were adjusted for various covariates, including gender, age, body mass index, footsteps, smoking status, drinking status, marital status, number of chronic diseases, number of medications, diabetes mellitus, hyperlipidemia, coronary artery disease, respiratory disease, and musculoskeletal disease and an interaction term between time and sleep duration.ResultsThe results of the generalized estimating equation showed a significant correlation (p < 0.001) between sleep duration of 8 h or more and low muscle mass in older adults, using 6–7 h of sleep as a reference. This effect was seen over time and prolonged sleep accumulated over multiple months had a greater effect on muscle mass loss than a single month. The effect of long sleep duration on muscle mass loss was significantly greater in females than in males and greater in the over-75 than in the under-75 age group. Restricted cubic spline plots showed a non-linear relationship between sleep duration and low muscle mass (p < 0.001).ConclusionsThis study found an association between sustained nighttime sleep of more than eight hours and decreased muscle mass in older adults, especially older women.

2D signal estimation for sparse distributed target photon counting data

In this study, we explore the utilization of penalized likelihood estimation for the analysis of sparse photon counting data obtained from distributed target lidar systems. Specifically, we adapt the Poisson Total Variation processing technique to cater to this application. By assuming a Poisson noise model for the photon count observations, our approach yields denoised estimates of backscatter photon flux and related parameters. This facilitates the processing of raw photon counting signals with exceptionally high temporal and range resolutions (demonstrated here to 50 Hz and 75 cm resolutions), including data acquired through time-correlated single photon counting, without significant sacrifice of resolution. Through examination involving both simulated and real-world 2D atmospheric data, our method consistently demonstrates superior accuracy in signal recovery compared to the conventional histogram-based approach commonly employed in distributed target lidar applications.

The value of biomarkers in the therapy of CRSwNP with biologicals-a long-term follow-up of dupilumab therapy.

Since its release, Dupilumab has shown great results in treating severe uncontrolled CRSwNP. However, there is a lack of real-world data beyond 12months of follow-up, and it is not clear to what extent biomarkers are appropriate for monitoring and predicting the Dupilumab therapy success. Hence, this study aims to analyze biomarkers for monitoring therapy, predicting therapy success and assess the effect of Dupilumab in real-world settings. The follow-up was performed with 104 patients retrospectively up to 22months, assessing SNOT-22, NPS, olfactometry, ACS, FEV-1, and blood biomarkers (total serum IgE, Eosinophils, ECP). Patients were divided into subgroups depending on their pretherapeutic biomarker levels and subsequent development was analyzed. There was substantially improvement in all clinical parameters up to 1year and then continuously up to month 22. Patients with initially elevated baseline blood eosinophil counts (> 0.5billion/L) had a trend of better SNOT-22 development after 1year (- 12.19 points, p = 0.03). The course of total serum IgE showed moderate correlation with almost all clinical variables obtained. Therapy was well tolerated with only mild and transient adverse events. Dupilumab has considerably reduced symptoms and disease severity even beyond 1year of treatment, supporting its role as targeted and effective treatment option for CRSwNP. Our data shows that total serum IgE is a promising biomarker for the monitoring during the treatment with Dupilumab. Elevated pre-therapeutic serum eosinophil counts may be a predictor of good subjective response to therapy. Larger cohorts and a long-term-follow-up over years are needed to further consolidate these findings.

Oncologic Outcomes for Different Axillary Staging Techniques in Patients with Nodal-Positive Breast Cancer Undergoing Neoadjuvant Systematic Treatment: A Cancer Registry Study.

Targeted approaches such as targeted axillary dissection (TAD) or sentinel lymph node biopsy (SLNB) showed false-negative rates of < 10% compared with axillary lymph node dissection (ALND) in patients with nodal-positive breast cancer undergoing neoadjuvant systemic treatment (NAST). We aimed to evaluate real-world oncologic outcomes for different axillary staging techniques. We identified nodal-positive breast cancer patients undergoing NAST from 2016 to 2021 from the state cancer registry of Baden-Wuerttemberg, Germany. Invasive disease-free survival (iDFS) was assessed using Kaplan-Meier statistics and multivariate Cox regression models (adjusted for age, ypN stage, ypT stage, and tumor biologic subtype). A total of 2698 patients with a median follow-up of 24.7 months were identified: 2204 underwent ALND, 460 underwent SLNB (255 with ≥ 3 sentinel lymph nodes [SLNs] removed, 205 with 1-2 SLNs removed), and 34 underwent TAD. iDFS 3 years after surgery was 69.7% (ALND), 76.6% (SLNB with ≥ 3 SLNs removed), 76.7% (SLNB with < 3 SLNs removed), and 78.7% (TAD). Multivariate Cox regression analysis showed no significant influence of different axillary staging techniques on iDFS (hazard ratio [HR] for SLNB with < 3 SLNs removed 0.96, 95% confidence interval [CI] 0.62-1.50; HR for SLNB with ≥ 3 SLNs removed 0.86, 95% CI 0.56-1.3; HR for TAD 0.23, 95% CI 0.03-1.64; ALND reference), and for ypN+ (HR 1.92, 95% CI 1.49-2.49), triple-negative breast cancer (HR 2.35, 95% CI 1.80-3.06), and ypT3-4 (HR 2.93, 95% CI 2.02-4.24). These real-world data provide evidence that patient selection for de-escalated axillary surgery for patients with nodal-positive breast cancer undergoing NAST was successfully adopted and no early alarm signals of iDFS detriment were detected.

Real-world data on the effectiveness of the meloxicam and pridinol combination for musculoskeletal pain

Real-world data on the effectiveness of the meloxicam and pridinol combination for musculoskeletal pain

Higher infection risk for JAK inhibitors tofacitinib and baricitinib compared to subcutaneous biological DMARDs.

Rheumatoid arthritis (RA) is usually treated with disease modifying antirheumatic drugs (DMARDs), including biological DMARDs (bDMARDs) and more recently, Janus kinase inhibitors (JAKi). Randomized trials suggest similar infection risks for JAKi and bDMARDs, but real-world data are scarce. From a nationally representative prescription database, adult RA patients starting a new JAKi or bDMARD between August 1st, 2018, and January 31st, 2021, were included. Prescriptions of antibiotic, antiviral or antifungal medication were used as proxy for infections. Infection incidence rates (IR) were compared between JAKi and bDMARDs and infection risks were estimated using multilevel Poisson regression adjusted for follow-up time and potential confounders and stratified for age < 65 and ≥ 65 years. In 14,989 patients, we identified 20,050 treatment episodes with either JAKi or bDMARDs. The infection IR was significantly higher in JAKi (48/100 patient years) compared bDMARDs (35/100 patient years, adjusted incidence rate ratio (IRR) 1.22, 95% CI 1.12-1.33). More herpes zoster infections were seen in JAKi compared to bDMARDs (adjusted IRR 2.65, 95% CI 1.94-3.60). No significant differences in infection IRs were found comparing JAKi baricitinib and tofacitinib. In older patients, infection IRs were higher, but IRRs were similar between age groups. In comparison to bDMARDs, JAKi are associated with a slightly higher infection risk and a higher risk of herpes zoster specifically. In older patients, infection IRs are higher but similar infection risks for JAKi and bDMARDs are observed. No differences in infection risk between tofacitinib and baricitinib were found. Key Points • Compared to bDMARDs, JAKi are associated with a slightly higher infection risk for all ages • An increased risk of herpes zoster in patients who use JAK inhibitors was confirmed • No significant differences in infection incidence were found between tofacitinib and baricitinib.

Analyzing Neoadjuvant Chemotherapy Effects in HER2-Low Breast Cancer: Real World Data.

Neoadjuvant chemotherapy (NAC) can be used as upfront therapy in aggressive breast cancer (BC). human epidermal growth factor receptor 2 (HER2)-low BC, defined as tumors scoring +1 or +2 on immunohistochemistry without HER2 gene amplification by in situ hybridization, lacks information on real-world data (RWD) outcomes, especially in the NAC setting. This subgroup, which does not reach the HER2 positive criteria due to its lower receptor expression, represents a distinct clinical category potentially requiring tailored therapeutic approaches. The objective of this study is to characterize patients with BC with HER2-low status who received NAC in a Brazilian public reference center for female tumors and key outcomes such as pathological complete response (pCR), overall survival (OS), and metastasis-free survival (MFS). A retrospective cohort study based on a large BC database from a reference cancer center in Brazil. Patients with BC that received NAC, diagnosed between 2011 and 2020, were included if they presented HER2-low status (defined as tumors scoring +1 or +2 on immunohistochemistry without HER2 gene amplification by in situ hybridization) and had complete data on outcomes. Clinical and demographicdata were collected, such as age, menopausal status, Ki-67, hormone receptorexpression and others. Key outcomes from the study comprised pCR (defined as ypT0/TIs/ypN0), overall survival, and metastasis-free survival (MFS). Survival analyses were conducted through the semiparametric Kaplan-Meier method to assess OS and MFS by pCR status, considering BC diagnosis as the index date. Overall, 297 patients were eligible and 141 were included in the study after matching the HER2-low definition. The pCR was seen in 18 out of 141 patients (12.7%). The median overall survival was 8.2 years, and the median MFS was 2.7 years. The OS of pCR was 83.4% and non-pCR was 58.1%; the DFS of pCR was 55.5% and non-pCR 40.6%. This study gives updated insights on pCR, OS, and MFS in women with HER2-low BC exposed to NAC.

A real-world pharmacovigilance analysis of the FDA adverse event reporting system events for polatuzumab vedotin

ABSTRACT Background Polatuzumab vedotin is the first antibody-drug conjugate approved by the US Food and Drug Administration (FDA) for patients with diffuse large B-cell lymphoma. This study evaluated adverse events (AEs) associated with polatuzumab vedotin by data mining of the FDA Adverse Event Reporting System (FAERS). Methods This study included AEs registered in FAERS between 2019 Q2 and 2023 Q2. Four algorithms were used to quantify the signals of polatuzumab vedotin-associated AEs, including reporting odds ratio, proportional reporting ratio, Bayesian confidence propagation neural network, and multi-item gamma Poisson shrinker. Results A total of 7,609,450 reports were collected from the FAERS database, and 1,388 reports of polatuzumab vedotin were identified as primary suspected AEs. Polatuzumab vedotin-associated AEs involved 26 organ systems. According to the four algorithms, 108 significant disproportionality AEs were retained simultaneously. Unexpected significant AEs included gastrointestinal hemorrhage, ileus, gastrointestinal perforation, cholecystitis, hypogammaglobulinemia, hepatitis B reactivation, hypercalcemia, hydronephrosis, cystitis hemorrhagic, interstitial lung disease, and thrombophlebitis. The median time to onset of polatuzumab vedotin-associated AEs was 20 (interquartile range 4–56) days. Conclusions Our study identified significant new AE signals for polatuzumab vedotin through real-world disproportionality analysis data and may provide additional evidence for risk identification of polatuzumab vedotin.

Challenges and Lessons Learned in Autologous Chimeric Antigen Receptor T-Cell Therapy Development from a Statistical Perspective.

Chimeric antigen receptor (CAR) T-cell therapy is a human gene therapy product where T cells from a patient are genetically modified to enable them to recognize desired target antigen(s) more effectively. In recent years, promising antitumor activity has been seen with autologous CAR T cells. Since 2017, six CAR T-cell therapies for the treatment of hematological malignancies have been approved by the Food and Drug Administration (FDA). Despite the rapid progress of CAR T-cell therapies, considerable statistical challenges still exist for this category of products across all phases of clinical development that need to be addressed. These include (but not limited to) dose finding strategy, implementation of the estimand framework, use of real-world data in contextualizing single-arm CAR T trials, analysis of safety data and long-term follow-up studies. This paper is the first step in summarizing and addressing these statistical hurdles based on the development of the six approved CAR T-cell products.

Estimating neutrosophic finite median employing robust measures of the auxiliary variable

Our study explores neutrosophic statistics, an extension of classical and fuzzy statistics, to address the challenges of data uncertainty. By leveraging accurate measurements of an auxiliary variable, we can derive precise estimates for the unknown population median. The estimators introduced in this research are particularly useful for analysing unclear, vague data or within the neutrosophic realm. Unlike traditional methods that yield single-valued outcomes, our estimators produce ranges, suggesting where the population parameter is likely to be. We present the suggested generalised estimator's bias and mean square error within a first-order approximation framework. The practicality and efficiency of these proposed neutrosophic estimators are demonstrated through real-world data applications and the simulated data set.

Disparities in PI3K/mTOR inhibitor use, toxicities, and outcomes among patients with metastatic breast cancer.

Novel agents such as PI3K and mTOR inhibitors (PI3K/mTORi) have expanded treatment options in metastatic breast cancer (MBC). Nevertheless, mortality rates remain disproportionately high for Black patients and patients with lower socioeconomic status. Furthermore, clinical trials for these novel agents lacked diversity, so their toxicity profile in minority populations is uncertain. We conducted a retrospective analysis of EHR-derived data from the Flatiron Health Database for patients with HR+, HER2- MBC. Multivariable logistic regression was used to evaluate factors associated with PI3K/mTORi use and toxicity outcomes. A total of 9169 patients with MBC were included in our analysis, of which 1780 (19.4%) received a PI3K/mTORi. We estimated the conditional total effect of insurance through Medicaid, and found lower odds of use of PI3K/mTORi among patients on Medicaid compared to those with commercial insurance (OR 0.73, 95% CI 0.54-0.99, p = 0.049). Odds of PI3K/mTORi use were higher for patients treated at an academic center (OR 1.28, CI 1.06-1.55, p = 0.01). Modeled as a controlled direct effect, Black/African American (Black/AA) race had no impact on odds of PI3K/mTOR use. Black/AA patients had twice the odds of developing hyperglycemia on PI3K/mTORi compared to White patients (OR 2.02, CI 1.24-3.39, p < 0.01). This analysis of real-world data suggests that the use of PI3K/mTORi is influenced by socioeconomic factors. We also found racial disparities in toxicity outcomes, with Black/AA patients having twice the risk of hyperglycemia. Our findings call for greater efforts to ensure access to novel treatments and improve their tolerability in diverse populations.

A novel non-negative Bayesian stacking modeling method for Cancer survival prediction using high-dimensional omics data

BackgroundSurvival prediction using high-dimensional molecular data is a hot topic in the field of genomics and precision medicine, especially for cancer studies. Considering that carcinogenesis has a pathway-based pathogenesis, developing models using such group structures is a closer mimic of disease progression and prognosis. Many approaches can be used to integrate group information; however, most of them are single-model methods, which may account for unstable prediction.MethodsWe introduced a novel survival stacking method that modeled using group structure information to improve the robustness of cancer survival prediction in the context of high-dimensional omics data. With a super learner, survival stacking combines the prediction from multiple sub-models that are independently trained using the features in pre-grouped biological pathways. In addition to a non-negative linear combination of sub-models, we extended the super learner to non-negative Bayesian hierarchical generalized linear model and artificial neural network. We compared the proposed modeling strategy with the widely used survival penalized method Lasso Cox and several group penalized methods, e.g., group Lasso Cox, via simulation study and real-world data application.ResultsThe proposed survival stacking method showed superior and robust performance in terms of discrimination compared with single-model methods in case of high-noise simulated data and real-world data. The non-negative Bayesian stacking method can identify important biological signal pathways and genes that are associated with the prognosis of cancer.ConclusionsThis study proposed a novel survival stacking strategy incorporating biological group information into the cancer prognosis models. Additionally, this study extended the super learner to non-negative Bayesian model and ANN, enriching the combination of sub-models. The proposed Bayesian stacking strategy exhibited favorable properties in the prediction and interpretation of complex survival data, which may aid in discovering cancer targets.

Chronicling menstrual cycle patterns across the reproductive lifespan with real-world data

The intricate hormonal and physiological changes of the menstrual cycle can influence health on a daily basis. Although prior studies have helped improve our understanding of the menstrual cycle, they often lack diversity in the populations included, sample size, and the span of reproductive and life stages. This paper aims to describe the dynamic differences in menstrual cycle characteristics and associated symptoms by age in a large global cohort of period-tracking application users. This work aims to contribute to our knowledge and understanding of female physiology at varying stages of reproductive aging. This cohort study included self-reported menstrual cycle and symptom information in a sample of Flo application users aged 18–55. Cycle and period length and their variability, and frequency of menstrual cycle symptom logs are described by the age of the user. Based on data logged by over 19 million global users of the Flo app, the length of the menstrual cycle and period show clear age-associated patterns. With higher age, cycles tend to get shorter (Cycle length: D¯\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\overline{\ ext{D}}}$$\\end{document} = 1.85 days, Cohen’s D = 0.59) and more variable (Cycle length SD: D¯\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\overline{\ ext{D}}}$$\\end{document} = 0.42 days, Cohen’s D = 0.09), until close to the chronological age (40–44) suggesting menopausal transition, when both cycles and periods become longer (Cycle length: D¯\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\overline{\ ext{D}}}$$\\end{document} = 0.86 days, t = 48.85, Cohen’s D = 0.26; Period length: D¯\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\overline{\ ext{D}}}$$\\end{document} = 0.08, t = 15.6, Cohen’s D = 0.07) and more variable (Cycle length SD: D¯\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\overline{\ ext{D}}}$$\\end{document} = 2.80 days, t = 111.43, d = 0.51; Period length SD: D¯\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\overline{\ ext{D}}}$$\\end{document} = 0.23 days, t = 67.81, Cohen’s D = 0.31). The proportion of individuals with irregular cycles was highest in participants aged 51–55 (44.7%), and lowest in the 36–40 age group (28.3%). The spectrum of common menstrual cycle-related symptoms also varies with age. The frequency of logging of cramps and acne is lower in older participants, while logs of headache, backache, stress, and insomnia are higher in older users. Other symptoms show different patterns, such as breast tenderness and fatigue peaking between the ages of 20–40, or mood swings being most frequently logged in the youngest and oldest users. The menstrual cycle and related symptoms are not static throughout the lifespan. Understanding these age-related differences in cycle characteristics and symptoms is essential in understanding how best to care for and improve the daily experience for menstruators across the reproductive life span.

Ideal cardiovascular health index and high-normal blood pressure in elderly people: evidence based on real-world data

Limited information is available on the cardiovascular health (CVH) index and risk of high-normal blood pressure (HNBP) in elderly people. Randomized cluster sampling, multivariate logistic regression, and mediating effects analysis were used in this study analyze the relationship between CVH index and HNBP in the elderly. 1089 non-hypertensive residents aged 65 years or older completed the study. The positive rate of HNBP was 75.85% (male vs. female: 76.13% vs. 75.64%, P = 0.852); The ideal rate of CVH (ideal CVH index ≥ 5 items) was 14.51% (male vs. female: 15.91% vs. 13.46%, P = 0.256). Compared with people with 0–2 ideal CVH index, the risk of HNBP in people with 4 ideal indexes and ≥ 5 ideal indexes decreased by 50% and 63%, respectively, and their OR (95% CI) were 0.50 (0.31, 0.81) and 0.37 (0.21, 0.66), respectively. The results of the trend test showed that the risk of HNBP decreased by 32% for every increase in the ideal CVH index (trend P < 0.001) and TyG index does not play a mediating role in this relationship. That is, increasing the number of ideal CVH index may effectively reduce the risk of HNBP in elderly by one-third.

Mining Real-World Big Data to Characterize Adverse Drug Reaction Quantitatively: Mixed Methods Study.

Adverse drug reactions (ADRs), which are the phenotypic manifestations of clinical drug toxicity in humans, are a major concern in precision clinical medicine. A comprehensive evaluation of ADRs is helpful for unbiased supervision of marketed drugs and for discovering new drugs with high success rates. In current practice, drug safety evaluation is often oversimplified to the occurrence or nonoccurrence of ADRs. Given the limitations of current qualitative methods, there is an urgent need for a quantitative evaluation model to improve pharmacovigilance and the accurate assessment of drug safety. In this study, we developed a mathematical model, namely the Adverse Drug Reaction Classification System (ADReCS) severity-grading model, for the quantitative characterization of ADR severity, a crucial feature for evaluating the impact of ADRs on human health. The model was constructed by mining millions of real-world historical adverse drug event reports. A new parameter called Severity_score was introduced to measure the severity of ADRs, and upper and lower score boundaries were determined for 5 severity grades. The ADReCS severity-grading model exhibited excellent consistency (99.22%) with the expert-grading system, the Common Terminology Criteria for Adverse Events. Hence, we graded the severity of 6277 standard ADRs for 129,407 drug-ADR pairs. Moreover, we calculated the occurrence rates of 6272 distinct ADRs for 127,763 drug-ADR pairs in large patient populations by mining real-world medication prescriptions. With the quantitative features, we demonstrated example applications in systematically elucidating ADR mechanisms and thereby discovered a list of drugs with improper dosages. In summary, this study represents the first comprehensive determination of both ADR severity grades and ADR frequencies. This endeavor establishes a strong foundation for future artificial intelligence applications in discovering new drugs with high efficacy and low toxicity. It also heralds a paradigm shift in clinical toxicity research, moving from qualitative description to quantitative evaluation.