Background Myotonic dystrophy (DM) is a rare, inherited disorder with multi-systemic effects that impact the skeletal muscles, eyes, heart, skin and gastrointestinal, endocrine, respiratory, and central nervous systems. DM is divided into two subtypes: DM1 can present from early childhood through adulthood and also has a congenital form (cDM) while DM2 typically manifests during mid-adulthood. Both forms are progressive with no approved treatments, and unmet need for disease-modifying therapies remains high. This study interrogated health insurance claims data to explore the clinical experience, healthcare resource utilization (HCRU), and all-cause costs for DM. Results A total of 8541 patients with DM and 242 patients with cDM and their matched controls were selected from a database of over 200 million claimants. HCRU and all-cause costs, including pharmacy, outpatient, and inpatient services, were analyzed across four years in 12-month follow-up periods. Mean all-cause costs per DM patient were high in each of the four periods (range $14,640–$16,704) and showed a steady increase from 13 to 23 months on, while the control group mean costs declined from $9671 in the first 12 months after the index event, to approach the US population average ($5193) over time. For cDM, the highest mean costs were in the first 12-months ($66,496 vs. $2818 for controls), and remained high (above $17,944) across all subsequent periods, while control mean costs approached $0. For DM and cDM, HCRU was higher compared to controls across all study periods and all-cause healthcare costs were mostly driven by inpatient and outpatient encounters. Analysis of all diagnosis codes over the study period (comorbidities) demonstrated an elevated comorbidity profile consistent with the clinical profile of DM. Conclusions This study is among the first to utilize claims data to increase understanding of the clinical experience and health economic outcomes associated with DM. The markedly elevated HCRU patterns and comorbidity profile presented here add to the broad body of scientific and clinical knowledge on DM. These insights can inform clinical care and support the development of disease modifying and/or symptom-targeting therapies that address the multi-systemic, progressive nature of DM.
Among women ≥ 50 years with fracture, 76% had not received osteoporosis diagnosis or treatment at 6 months and only 14% underwent a DXA scan. Nearly half of all and 90% of hip fracture patients required surgery. Fractures cause substantial clinical burden and are not linked to osteoporosis diagnosis or treatment. Purpose Osteoporosis (OP) and OP-related fractures are a major public health concern, associated with significant economic burden. This study describes management patterns following a nontraumatic fracture for commercially insured patients. Methods This retrospective cohort study identified women aged ≥ 50 years having their first nontraumatic index fracture (IF) between January 1, 2015 and June 30, 2019, from IQVIA’s PharMetrics® Plus claims database. Medical management patterns at month 6 and medication use patterns at months 6, 12, and 24 following the IF were described. Results Among 48,939 women (mean ( SD ) age: 62.7 (9.5) years), the most common fracture types were vertebral (30.6%), radius/ulna (24.9%), and hip (HF; 12.1%). By month 6, 76% of patients had not received an OP diagnosis or treatment, 13.6% underwent a DXA scan, and 11.2% received any OP treatment. Surgery was required in 43.1% of all patients and 90.0% of HF patients on or within 6 months of the fracture date. Among HF patients, 41.4% were admitted to a skilled nursing facility, 96.7% were hospitalized an average of 5.5 days, and 38.1% required durable medical equipment use. The 30-day all-cause readmission rate was 14.3% among those hospitalized for the IF. Overall, 7.4%, 9.9%, and 13.2% had a subsequent fracture at months 6, 12, and 24, respectively. Conclusion Our findings provide an overview of post-fracture management patterns using real-world data. OP was remarkably underdiagnosed and undertreated following the initial fracture. Nontraumatic fracture, particularly HF, resulted in substantial ongoing clinical burden.
Background: Chronic obstructive pulmonary disease (COPD) shares common risk factors with digestive tract malignancies such as esophageal cancer. However, the prevalence and geographic distribution of COPD in patients with CI-cancer is only poorly understood. Methods: We used the IQVIA's Oncology Dynamics (OD) database to identify a total of 48,061 patients with GI cancer (4,229 esophagus, 7,568 stomach, 27,300 colon, and 8,964 rectum cancer) from Germany, France, Italy, Spain and the UK. Results: The prevalence of COPD among the 48,061 patients with GI cancer was 12.5% (5,983/48,061). We observed significant differences in frequencies of COPD between the different cancer sites with the highest COPD prevalence among patients with esophageal (25.5%) or gastric cancer (13.4%) and lowest prevalence in colon (11.0%) or rectal (9.8%) cancer patients. Moreover, rates of COPD strongly varied between digestive tract cancer patients from different countries. Interestingly, Spain (16.8%) and Germany (13.4%) had the highest COPD prevalence while prevalence of COPD was lowest in the UK (8.4%). Finally, we showed that the proportion of digestive tract cancer patients with COPD was highest among male patients (15%) and those >80 years (20.6%) when compared to all other patients. Conclusions: In this analysis, we show that COPD is found at high frequencies in patients with digestive tract cancer in Europe. We demonstrate that prevalence varies according to digestive tract cancer sites and European countries.
Aims Previous observational studies on glucose-lowering drugs and risk of stroke in type 2 diabetes yielded conflicting results. The aim was to examine the association of glucose-lowering drugs with incident stroke and transient ischaemic attacks (TIA) in newly diagnosed type 2 diabetes. Methods We conducted a retrospective cohort analysis of the disease analyzer, which comprises a representative panel of 1248 general and internal medicine practices throughout Germany (01/2000–12/2019: 9.8 million patients). Incident non-fatal stroke/TIA was defined based on ICD-10 codes (I53, I64; G45) in newly diagnosed type 2 diabetes. Cox regression models were fitted to obtain hazard ratios (HR; 95%CI) for stroke/TIA adjusting for potential confounders (age, sex, health insurance, coronary heart disease, myocardial infarction, heart failure, polyneuropathy, blood pressure, eGFR) and anthropometric and metabolic intermediators (BMI, HbA1c, HDL- and LDL-cholesterol, triglycerides, lipid-lowering drugs). Result 312,368 persons with newly diagnosed type 2 diabetes without previous stroke/TIA (mean age: 64 years; 52% males) were included. There were 16,701 events of non-fatal stroke/TIA corresponding to an incidence rate of 9.3 (95%CI 9.1–9.4) per 1000 person-years. Using Cox regression, adjusted HR for stroke/TIA (per 1 year of treatment) of 0.59 (0.54–0.64) for SGLT2 inhibitors and of 0.79 (0.74–0.85) for GLP-1 receptor agonists were estimated. DPP-4 inhibitors (0.84; 0.82–0.86), metformin (0.90; 0.89–0.91), insulin (0.92; 0.91–0.93) and sulfonylureas (0.98; 0.96–0.99) also showed moderately reduced HR for stroke/TIA. Sex-specific regression analyses yielded similar results (HR). Conclusions Treatment with SGLT2 inhibitors or GLP-1 receptor agonists might reduce non-fatal stroke/TIA in persons with newly diagnosed type 2 diabetes.
Background: The prognosis of colorectal cancer (CRC) patients is determined to a decisive extent by comorbidities. On the other hand, anti-cancer treatments for CRC are associated with relevant toxicities and may therefore cause additional comorbidities. Methods: This retrospective cohort study assessed the prevalence of various diseases in patients 12 months before and 12 months after an initial diagnosis of colorectal cancer (ICD-10: C18, C20) in 1274 general practices in Germany between January 2000 and December 2018. The study is based on the Disease Analyzer database (IQVIA), which contains drug prescriptions, diagnoses, and basic medical and demographic data. Patients with and without CRC were matched by sex, age, and index year. Results: We identified several diagnoses with a significantly higher prevalence among CRC patients 12 months prior to the index date compared to controls. These diagnoses included gastrointestinal hemorrhage, hemorrhoids, perianal venous thrombosis, and abdominal and pelvic pain, as well as functional intestinal disorders. In contrast, the prevalence of lipid metabolism disorder, depression, hypertension, coronary heart disease, or acute bronchitis was significantly lower in CRC cases. After diagnosis of CRC, we found a significantly higher prevalence of anemia, polyneuropathies, functional intestinal disorders, and chronic kidney disease among CRC patients compared to the control group, while the prevalence of acute upper respiratory infections of multiple and unspecified sites and acute bronchitis was significantly lower in CRC patients compared to non-CRC patients. Conclusions: In the present study, we identified a variety of diseases occurring at higher or lower frequencies in CRC patients compared to matched controls without CRC. This might help to select patients for early CRC screening and improve the clinical management of CRC patients.
Purpose Quality of life research often collects daily information and averages this over a week, producing a summary score. When data are missing, arbitrary rules (such as requiring at least 4/7 observations) are used to determine whether a patient’s summary score is created or set to missing. This simulation work aimed to assess the impact of missing data on the estimates produced by summary scores, the psychometric properties of the resulting summary score estimates and the impact on interpretation thresholds. Methods Complete longitudinal data were simulated for 1000 samples of 400 patients with different day-to-day variability. Data were deleted from these samples in line with missingness mechanisms to create scenarios with up to six days of missing data. Summary scores were created for complete and missing data scenarios. Summary score estimates, psychometric properties and meaningful change estimates were assessed for missing data scenarios compared to complete data. Results In most cases, the 4/7 day rule was supported, but this depended on daily variability. Fewer days of data were sometimes acceptable, but this was also dependent on the proportion of patients with missing data. Tables and figures allow researchers to assess the potential impact of missing data in their own studies. Conclusions This work suggests that the missing data rule used to create summary scores impacts on the estimate, measurement properties and interpretation thresholds. Although a general rule of 4/7 days is supported, the way the summary score is derived does not have a uniform impact across psychometric analyses. Recommendations are to use the 4/7 rule, but plan for sensitivity analyses with other missing data rules.
Digital health technologies such as wearable sensors are increasingly being used in clinical trials. However, the endpoints created from these useful tools are wide and varied. Often, digital health technologies such as wearable sensors are used either to collect a raw metric like "step count" or with artificial intelligence algorithms to define a biomarker for improvement. In the case of the former, improvements in such a raw metric is difficult to attribute to the patient health in a meaningful way. In the case of the latter, despite the potential predictive accuracies of machine learning and artificial intelligence approaches, the resulting biomarkers are a black box, which has limited direct interpretability to the patient's specific health concerns. The paper represents a call to arms to really place the patient at the heart of the endpoint. By designing trial endpoints which are measured by digital health technologies using a patient centered approach from the outset, the patient benefits from understanding the implications of approved medication for their life.
Background: Inflammatory bowel disease (IBD) is of high medical and socioeconomic relevance. Moderate and severe disease courses often require treatment with biologics. The aim of this study was to evaluate machine learning (ML)-based methods for the prediction of biologic therapy in IBD patients using a large prescription database. Methods: The present retrospective cohort study utilized a longitudinal prescription database (LRx). Patients with at least one prescription for an intestinal anti-inflammatory agent from a gastroenterologist between January 2015 and July 2021 were included. Patients who had received an initial biologic therapy prescription (infliximab, adalimumab, golimumab, vedolizumab, or ustekinumab) were categorized as the "biologic group". The potential predictors included in the machine learning-based models were age, sex, and the 100 most frequently prescribed drugs within 12 months prior to the index date. Six machine learning-based methods were used for the prediction of biologic therapy. Results: A total of 122,089 patients were included in this study. Of these, 15,824 (13.0%) received at least one prescription for a biologic drug. The Light Gradient Boosting Machine had the best performance (accuracy = 74%) and was able to correctly identify 78.5% of the biologics patients and 72.6% of the non-biologics patients in the testing dataset. The most important variable was prednisolone, followed by lower age, mesalazine, budesonide, and ferric iron. Conclusions: In summary, this study reveals the advantages of ML-based models in predicting biologic therapy in IBD patients based on pre-treatment and demographic variables. There is a need for further studies in this regard that take into account individual patient characteristics, i.e., genetics and gut microbiota, to adequately address the challenges of finding optimal treatment strategies for patients with IBD.
Background: Real-world estimates of relapsed or refractory (R/R) acute myeloid leukemia (AML) chemotherapy episode costs are scarce. We quantified chemotherapy episode-related costs and healthcare resource use (HRU) in R/R AML. Research design and methods: This real-world, retrospective analysis of United States claims from IQVIA's PharMetrics® Plus database (October 2008-September 2019) identified adults with R/R AML and ≥1 chemotherapy episode. Chemotherapy episode (ie, low- [LIC] or high-intensity [HIC] chemotherapy) costs and HRU were determined using inpatient, outpatient, and pharmacy claims. Results: Mean (SD) and median total all-cause healthcare costs per R/R AML chemotherapy episode were $230,799 ($300,770) and $129,117. Mean (SD) and median adjusted direct R/R AML chemotherapy episode costs were $116,384 ($151,425) and $63,298, with increases noted from the first to the second and subsequent episodes and with HIC. Hospitalizations were the major cost driver; 64.1% of patients had ≥1 hospitalization and 36% required an intensive care unit stay. Conclusions: R/R AML chemotherapy episode costs were high, with higher costs reported with HIC and increasing lines of chemotherapy. Hospitalizations were a main cost driver. Novel therapies with comparable or improved effectiveness and decreased need for hospitalizations versus chemotherapy may help alleviate the clinical and economic burden of R/R AML.
Objective To ascertain the completeness of reporting of uveal melanoma cases in North Carolina to the state’s cancer registry. Methods This was a retrospective chart review performed at a single institution analyzing the completeness of information reported to the North Carolina Cancer Registry between 2010 and 2015. A list of all patients with uveal melanoma diagnosed, treated and/or followed at UNC-Chapel Hill between 2010-2015 was compared to the list of patients with uveal melanoma reported to the North Carolina Central Cancer registry during the same time frame. Results Based on ICD 9 and 10 codes, there were 66 patients with ciliary body or choroidal melanomas diagnosed, followed and/or treated at UNC between 2010 and 2015. Of those, 41 (62%) were on the list of cases reported through the UNC Cancer Registry to the NCCCR. A chart review of the excluded cases was performed and the following barriers to reporting of uveal melanoma were identified: lack of diagnostic imaging results, lack of histopathologic confirmation, inconsistent language used to communicate diagnosis, and lack of implementation of the North American Association of Central Cancer Registries’ National Interstate Data Exchange Agreement. Conclusion The diagnosis and treatment of uveal melanoma is unique when compared to other types of cancers. Diagnosis is based on clinical features and characteristic findings on ophthalmic imaging and ultrasound. There is often no pathology report or radiologic imaging which makes it difficult for hospital registrars to recognize and confirm cases of uveal melanoma. This creates significant barriers to reporting cases to state and national cancer registries. The incomplete data makes it difficult to detect changes in the incidence of uveal melanoma in North Carolina. The development of a national uveal melanoma registry should be seriously considered.
Background The pathogenesis of multiple sclerosis (MS) has not yet been fully uncovered. There is increasing evidence that Epstein-Barr-Virus (EBV) infection, which affects over 90% of people during life and causes infectious mononucleosis, leads to an increased incidence of MS, and thus may play a crucial role in the pathophysiology of the disease. Methods Using the Disease Analyzer database (IQVIA) featuring diagnoses as well as basic medical and demographic data of outpatients from general practices in Germany, we identified a total of 16,058 patients with infectious mononucleosis that were matched to a cohort of equal size without infectious mononucleosis based on patients’ age, sex, index year and yearly consultation frequency. Incidence of MS was compared within a 10-year follow-up period. Results Within 10 years from the index date, the incidence of MS was 22.6 cases per 100,000 person-years among patient with infectious mononucleosis but only 11.9 cases per 100,000 person-years among individuals without infectious mononucleosis. In regression analysis, infectious mononucleosis was significantly associated with the incidence of MS (HR: 1.86, 95% CI: 1.09-3.16). Subgroup analysis revealed the strongest association between infectious mononucleosis and MS in the age group between 14 and 20 years (HR: 3.52, 95% CI: 1.00-12.37) as well as a stronger association in men compared to women. Conclusion Infectious mononucleosis is associated with an increased incidence of MS especially in younger individuals. Our data support the growing evidence of a decisive involvement of EBV in the currently unknown pathophysiology of MS and should trigger further research efforts to better understand and potentially prevent cases of this disabling disease in future.
Purpose The clinical relevance of different time-to-deterioration (TTD) definitions for patient-reported outcomes were explored. Methods TTD definitions differing by reference score and deterioration event were used to analyse data from the phase 3 FLAURA trial of first-line osimertinib versus erlotinib or gefitinib in patients with EGFR-mutated advanced non-small cell lung cancer. Pre-specified key symptoms were fatigue, appetite loss, cough, chest pain and dyspnoea, scored using the European Organisation for Research and Treatment of Cancer QLQ-C30 and QLQ-LC13 questionnaires (≥ 10-point difference = clinically relevant). Results No significant treatment differences in TTD (distributions) were observed using definitions based on transient or definitive deterioration alone. TTD definitions based on definitive, sustained deterioration, with death not included as an event, yielded a significant treatment difference for dyspnoea (hazard ratio [HR] 0.71; P = 0.034) when baseline was the reference, and for cough (HR 0.70; P = 0.009) and dyspnoea (HR 0.71; P = 0.004) when best previous score was the reference. With death included as an event, treatment differences were significant for dyspnoea (HR 0.70; P = 0.025) when baseline was the reference, and for cough (HR 0.70; P = 0.011), dyspnoea (HR 0.71; P = 0.003) and chest pain (HR 0.71; P = 0.038) when best previous score was the reference. Irrespective of definition, TTD for appetite loss and fatigue did not differ significantly between arms. Conclusion This exploratory work showed that different TTD definitions yield different magnitudes of treatment difference, highlighting the importance of pre-specifying TTD definitions upfront in clinical trials. Clinical trial registration ClinicalTrials.gov NCT02296125.
Purpose: The aim of the present study was to determine whether women diagnosed with breast cancer (BC) have an increased incidence of other cancers, e.g., gastric cancer, lung cancer, skin cancer, and so on, compared to healthy women without a breast cancer diagnosis. Methods: This retrospective cohort study was based on data from the Disease Analyzer database (IQVIA) and included adult women with an initial diagnosis of BC documented in one of 1,274 general practices in Germany between January 2000 and December 2018. Women with BC were matched to women without cancer by age, index year, yearly consultation frequency, and co-diagnoses. Univariate Cox regression models were used to study the association between BC and the incidence of other cancer diagnoses. Results: 21,124 women with BC and 21,124 women (mean age: 63 years) without cancer were included. Within 10 years of the index date, 14.3% of women with BC and 10.0% of women without cancer were diagnosed with cancer (p < 0.001). BC was significantly associated with the incidence of other cancer diagnoses (HR: 1.42, p < 0.001). The strongest association was observed for respiratory organ cancer (HR = 1.69, p < 0.001), followed by female genital organ cancer (HR = 1.61, p < 0.001) and cancer of lymphoid and hematopoietic tissue (HR: 1.59, p < 0.001). Conclusion: The results of this study show that women with BC have an increased incidence of another cancer compared to women without cancer. Therefore, it is important to pay particular attention to the development of other malignancies during follow-up in patients with BC. This should be considered especially in patients with a proven genetic mutation.
Aims It is now understood that almost half of newly diagnosed cases of type 1 diabetes are adult-onset. However, type 1 and type 2 diabetes are difficult to initially distinguish clinically in adults, potentially leading to ineffective care. In this study a machine learning model was developed to identify type 1 diabetes patients misdiagnosed as type 2 diabetes. Methods In this retrospective study, a machine learning model was developed to identify misdiagnosed type 1 diabetes patients from a population of patients with a prior type 2 diabetes diagnosis. Using Ambulatory Electronic Medical Records (AEMR), features capturing relevant information on age, demographics, risk factors, symptoms, treatments, procedures, vitals, or lab results were extracted from patients' medical history. Results The model identified age, BMI/weight, therapy history, and HbA1c/blood glucose values among top predictors of misdiagnosis. Model precision at low levels of recall (10%) was 17%, compared to <1% incidence rate of misdiagnosis at the time of the first type 2 diabetes encounter in AEMR. Conclusions This algorithm shows potential for being translated into screening guidelines or a clinical decision support tool embedded directly in an EMR system to reduce misdiagnosis of adult-onset type 1 diabetes and implement effective care at the outset.
Objectives To describe the impact of immune checkpoint inhibitors (ICIs) on treatment patterns and survival outcomes in patients with locally advanced or metastatic non-small cell lung cancer (aNSCLC) in France and Germany. Materials and Methods Patients with aNSCLC without known ALK or EGFR mutations receiving first-line (1L) therapy were included from (i) the retrospective Epidemiological-Strategy and Medical Economics Advanced and Metastatic Lung Cancer cohort (ESME-AMLC, France; 2015–2018) and (ii) the prospective Clinical Research platform Into molecular testing, treatment and outcome of non-Small cell lung carcinoma Patients platform (CRISP, Germany; 2016–2018). Analyses were stratified according to histology. Survival outcomes were estimated using Kaplan–Meier methodology and stratified by year of 1L therapy. Data sources were analysed separately. Results In ESME-AMLC and CRISP, 8,046 and 2,359 patients were included in the study, respectively. In both countries, approximately 20% of all patients received pembrolizumab monotherapy as 1L treatment in 2018. In ESME-AMLC, the proportion receiving an ICI over the course of treatment (any line) increased from 42.2% (2015) to 56.1% (2018) in patients with squamous histology, and 28.9% to 51.9% with non-squamous/other; in CRISP, it increased from 50.6% (2016) to 65.2% (2018) with squamous histology, and 40.8% to 62.7% with non-squamous/other. Two-year overall survival from 1L initiation was 36.8% and 25.6% in the squamous cohorts and 36.5% and 30.8% in the non-squamous/other cohorts in ESME-AMLC and CRISP, respectively. No significant change in overall survival was observed over time; however, the follow-up time available was limited in the later years of the analysis. Conclusion The results of this joint research from two large clinical databases in France and Germany demonstrate the growing use of ICIs in the management of aNSCLC. Future analyses will allow for the evaluation of the impact of ICIs on long-term survival of patients with aNSCLC.
Clinical trials for Alzheimer's disease (AD) are slower to enroll study participants, take longer to complete, and are more expensive than trials in most other therapeutic areas. The recruitment and retention of a large number of qualified, diverse volunteers to participate in clinical research studies remain among the key barriers to the successful completion of AD clinical trials. An advisory panel of experts from academia, patient‐advocacy organizations, philanthropy, non‐profit, government, and industry convened in 2020 to assess the critical challenges facing recruitment in Alzheimer's clinical trials and develop a set of recommendations to overcome them. This paper briefly reviews existing challenges in AD clinical research and discusses the feasibility and implications of the panel's recommendations for actionable and inclusive solutions to accelerate the development of novel therapies for AD.
Background Adenosine deaminase deficiency (ADA) is a primary autosomal recessive genetic disorder leading to severe combined immunodeficiency (SCID). It is characterized pathophysiologically by intracellular accumulation of toxic products affecting lymphocytes and other organ systems. This cross sectional study was conducted to describe the liver disease in a cohort of patients with autosomal recessive ADA-SCID. Methods A single center cross sectional retrospective analysis (2006 to 2019) was performed in 18 patients with genetically confirmed ADA-SCID. Liver disease was defined as ≥1.5x the gender specific upper limit of normal (ULN; 33 IU/L for males and 25 IU/L for females) or moderate and severe increase in liver echogenicity on ultrasound. Results The cohort included 11 males, the median age was 11.5 (3.5–30.0 years) and median BMI was 18.4 kg/m2. Eighteen (100%), Seven (38%) and five (27%) patients had enzyme replacement therapy (ERT), gene therapy (GT) and hematopoietic stem cell transplant (HSCT). Five (?%) patients had ALT levels more than 1.5x the ULN. Liver echogenicity was increased mildly in 6 (33%), moderately in 2 (11%), severely in 2 (11%) and normal in 8 (44.4%) patients. All patients had normal FIB-4 and NAFLD fibrosis score indicating absence of advanced fibrosis in our cohort. Of 8 patients who had liver biopsies for diagnostic purposes, steatohepatitis measured by histopathology NASH-CRN scoring was noted in 4 patients. Discussion Non-immunologic manifestations of ADA-SCID have become more apparent in recent years as survival improved. In our cohort, the most common liver disease manifestation was steatosis. We postulate that hepatic steatosis noted is possibly multifactorial - recurrent infection, exposure to multiple medications and increased BMI.
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