Optimal teicoplanin dosing regimen in neonates and children developed by leveraging real-world clinical information

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Takaaki Yamada ◽  
Chie Emoto ◽  
Tsuyoshi Fukuda ◽  
Yoshitomo Motomura ◽  
Hirosuke Inoue ◽  
...  
Keyword(s):  
Real World ◽  
Clinical Information ◽  
Dosing Regimen

ENETS single center of excellence experience with the NETest: A real-world assessment of 565 patients.

2020 ◽  
Vol 38 (4_suppl) ◽  
pp. 605-605
Author(s):  
Anna Malczewska ◽  
Mateusz Rydel ◽  
Amanda Robek ◽  
Katarzyna Kusnierz ◽  
Izabela Les-Zielinska ◽  
...  
Keyword(s):  
Real World ◽  
Clinical Status ◽  
Unmet Need ◽  
Clinical Information ◽  
Disease Status ◽  
Diagnostic Sensitivity ◽  
Lung Cancers ◽  
Center Of Excellence ◽  
Mcnemar’S Test ◽  
Mcnemar's Test

605 Background: There is a substantial clinical unmet need for an accurate and effective blood biomarker of NET disease. We therefore evaluated under real-world conditions the clinical utility of the NETest in a NET Center of Excellence and compare it with the biomarker CgA. Methods: Cohorts: GEP-NET (253), BP-NET (49), colon cancer (37), lung cancers (80), benign lung disease (59) and controls (86). GEP-NETs: 164 (65%) had image-detectable disease or were resection-margin (R1) positive. Grading included G1 [106], G2 [49] and G3 [9]. BP-NETs, 28 of 49 (57%) had evidence of disease. Grading was TC [14], AC [14]. Disease status (stable [SD] or progressive [PD]) determined by RECIST 1.1. Blood sampling: NETest ( n= 565) and NETest/CgA matched samples (135). NETest (PCR) (0-100 score) with positive > 20; progressive > 40. CgA (ELISA). All samples deidentified, and measurement/ analyses blinded. Statistics: Mann-Whitney U-test, McNemar’s test and AUROC. Results: GEPNET: NETest was significantly higher (34.4±1.8, p< 0.0001) in NET disease versus no NET disease (10.5±1, p< 0.0001), non-NET disease (18±4, p= 0.0004) or controls (7±0.5, p< 0.0001). Diagnostic sensitivity was 89%, and specificity 94%. NETest levels were not related to grade (G1: 32±2 vs. G2: 38±3, p= 0.09). BPNET: NETest was significantly higher (30±1.3) vs no NET disease (24.1±1.3, p= 0.0049). Diagnostic sensitivity 100%. Levels were elevated vs controls ( p< 0.0001) and non-NET disease (20±2, p= 0.0001). NETest levels were not related to grade (TC 30±2 vs. AC: 30±2, p= NS). Levels were elevated in PD (55±5.5) vs SD (33.6±2, p= 0.0005). AUCs for detecting disease ranged between 0.89 (GEP-NET) to 1.0 (BE-NET) ( p< 0.0001). Matched GEP-NETS (135): NETest was significantly more accurate for detecting NETS (99%) than CgA (53%, McNemar’s test Chi2= 87, p= 0.0001). sensitivity (99%) and specificity (96%) were better than CgA (37% and 96% respectively). Conclusions: The NETest is an accurate diagnostic test for both GEP- and BP-NEN. It defines clinical status (stable or progressive disease). NETest is significantly more accurate than CgA. The multianalyte genomic blood assessment of NET disease provided clinical information of utility in management.

OP08 Using Real World Data To Support National Postmarketing Surveillance

2018 ◽  
Vol 34 (S1) ◽  
pp. 3-3
Author(s):  
Yeqin Zuo ◽  
Bernie Mullen ◽  
Rachel Hayhurst ◽  
Karen Kaye ◽  
Renee Granger ◽  
...  
Keyword(s):  
Primary Care ◽  
Real World ◽  
National Level ◽  
Clinical Information ◽  
Health Priorities ◽  
Care Practice ◽  
Postmarketing Surveillance ◽  
Care Practices ◽  
Primary Care Practices ◽  
Tract Infections

Introduction:While medicines and medical tests are developed in a controlled clinical trial environment, postmarketing surveillance in the real world can be challenging. MedicineInsight—a database of longitudinal patient-level clinical information from primary care practices in Australia—is a novel program that collects primary care data to improve postmarketing surveillance at a national level.Methods:MedicineInsight collects de-identified clinical information from primary care practice information systems using data extraction tools. MedicineInsight currently includes 3.6 million regular patients of 3,300 family physicians (general practitioners) from 650 primary care practices across Australia. MedicineInsight data include longitudinal clinical information on diagnosis and medicines (dose, strength, route of administration, medication switches over time, adverse events, and allergies), and pathology testing data. A series of observational studies was developed for postmarketing surveillance of management of a range of health priorities including type 2 diabetes mellitus (T2DM), chronic obstructive pulmonary disease (COPD), depression, and antibiotics use.Results:Forty-four percent of patients with T2DM in the MedicineInsight database did not have a recorded hemoglobin A1c result and thirty-one percent did not have a recorded blood pressure reading in the previous 6 months. While guidelines recommend a stepwise approach to the initiation of COPD therapy, forty-nine percent of patients with COPD (with or without asthma) were prescribed dual therapy at initiation and a small number (4.5 percent) were prescribed triple therapy. Between 2011 and 2015, the annual rate of antidepressant prescribing per 1,000 family physician encounters increased by eight percent. High volumes of antibiotics were prescribed for respiratory tract infections in Australian primary care, notwithstanding guideline recommendations that antibiotics are not recommended in most cases.Conclusions:Large scale, real-world clinical data from primary care practices can play an important role in postmarketing surveillance at a national level.

Evaluation of treatment patterns and outcomes in patients diagnosed with genitourinary (GU) cancers with linked claims plus prior authorization data.

2021 ◽  
Vol 39 (6_suppl) ◽  
pp. 284-284
Author(s):  
Lincy S. Lal ◽  
Caitlin Elliott ◽  
Stephanie Korrer ◽  
Stacey DaCosta Byfield ◽  
Benjamin Chastek ◽  
...  
Keyword(s):  
Resource Utilization ◽  
Median Duration ◽  
Real World ◽  
Claims Data ◽  
Clinical Information ◽  
Treatment Patterns ◽  
Cancer Type ◽  
Research Database ◽  
Prior Authorization ◽  
Line Of Therapy

284 Background: Integration of clinical and claims data allows for the examination of outcomes and characteristics which is essential for real world evidence generation and clinical decision making. We describe utilization of clinical data collected from an oncology Prior Authorization (PA) program integrated with claims data to evaluate treatment patterns, resource utilization, and total costs of care during therapy for patients with newly diagnosed metastatic and non-metastatic renal (R), bladder (B), and testicular (T) cancers. Methods: Commercially insured patients with a GU cancer diagnosis, from 2/2016 to 12/2019 with both clinical information from a PA tool (based on NCCN guidelines) and claims from the Optum Research Database were identified. Demographics, clinical information (metastatic status and line of therapy), treatment duration, resource utilization, and all-cause costs were collected, and uploaded to a dynamic web-based Tableau dashboard. Analysis was conducted for non-metastatic and metastatic settings based on the first observed treatment episode. Drug additions or switches incremented line of therapy; single drug discontinuations did not. All cost data were adjusted to 2019 values. Results: A total of 3,736 patients were included; 13% were censored (i.e. on treatment at the end of the study period). 916 patients (25%) were metastatic and 2,820 (75%) were in their adjuvant/neoadjuvant (A/N) line. 60% of the population was ≥55 years old and 85% were male. The top regimen in A/N line for each cancer type were: nivolumab (R), BCG(B), bleomycin + carboplatin/cisplatin+ etoposide (T). The top regimen in metastatic cancer were: nivolumab (R), carboplatin/cisplatin + gemcitabine (B), bleomycin + carboplatin/cisplatin + etoposide (T). The median duration of A/N line ranged from 50(B) to 119(R) days while the median duration for metastatic line range from 71(T) to 82(R) days. The highest rate of inpatient admissions was observed in patients with R (31%). Of the three cancers, R was the most expensive in the A/N and metastatic settings with mean (standard deviation) costs of $192,308 ($269,358) and $136,293 ($146,632), respectively. Conclusions: Combination of clinical and claims data provide valuable information on real world outcomes in routine clinical care and may support treatment selection decisions at the point of care.

scholarly journals Interim Results of the Observational Study Caro: Twice Weekly Carfilzomib Is a Convenient Treatment Option for Patients with Multiple Myeloma Who Have Received at Least One Prior Therapy

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 5662-5662
Author(s):  
Wolfgang Knauf ◽  
Andreas Ammon ◽  
Jens Uhlig ◽  
Marie Merling ◽  
Hans-Juergen Hurtz ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Treatment Option ◽  
Real World ◽  
Interim Analysis ◽  
Dose Intensity ◽  
Recommended Dose ◽  
Treatment Recommendation ◽  
Dosing Regimen ◽  
Dosing Schedule ◽  
Prior Therapy

Abstract Introduction: Poor adherence and persistence to anticancer treatment are serious issues in the management of cancer patients since nonadherence has been shown to lead to higher treatment failure rates, worse outcome and higher total costs of care. The combination of the proteasome inhibitor carfilzomib (Kyprolis®) with lenalidomide (Revlimid®) and dexamethasone (CAR/LEN/DEX) or with dexamethasone alone (CAR/DEX) is approved for the treatment of patients with multiple myeloma who have received at least one prior therapy. According to the current approved schedule, carfilzomib has to be given twice weekly in both regimens. Real-world data on the implementation of this treatment recommendation are still limited. Methods: The prospective, multicenter, non-interventional, observational CARO study was designed to collect data on 300 patients with multiple myeloma (CAR/LEN/DEX: 200, CAR/DEX: 100) from 90 sites across Germany. Primary objective is patients' adherence and persistence to carfilzomib therapy as prescribed by the treating physician according to current Summary of Product Characteristics (SmPC). Secondary objectives are patients' adherence and persistence to lenalidomide and dexamethasone as well as the real-world implementation of the recommended CAR/LEN/DEX or CAR/DEX dosing regimen in clinical routine (i.e., the comparison of actually administered medication versus recommended medication according to current SmPC). Exploratory objectives are effectiveness, safety and health-related quality of life. The first interim analysis of the CARO study was scheduled to assess the primary and secondary endpoints 12 months after the recruitment of the first patient. Results: Between October 2016 and October 2017, 102 patients had been enrolled, thereof 68 patients into the CAR/LEN/DEX cohort and 32 patients into the CAR/DEX cohort at the time of the pre-specified interim analysis (database cut: 25 October 2017). Here, the focus is on the adherence of the twice weekly carfilzomib schedule in evaluable patients who received CAR/LEN/DEX (N=64) and on the implementation of the SmPC in terms of timing, dosing and frequency. Median age of patients was 72.3 years (range 43.4-84.3), 45.3% were female and 70.3% of the patients had a good performance status (PS) with a Karnofsky PS score of 80 to 100. The relative mean dose intensity of carfilzomib was 88.1%. 1368 of the scheduled 1591 carfilzomib administrations (86.0%) were given in time. 7.9% (n=125) of administrations were omitted, 5.0% (n=80) of administrations were delayed and 1.1% (n=18) of doses were administered earlier. Carfilzomib was omitted at least once in 43.8% of patients (n=28). 62.5% (n=40) and 18.8% (n=12) of patients, respectively, had a delayed or earlier carfilzomib administration documented at least once during their course of treatment. Reasons for deviations from the recommended carfilzomib dosing schedule concerning timing are depicted in Table 1. 1328 of 1466 carfilzomib administrations (90.6%) were given at the recommended dose. 6.2% (n=91) of doses were reduced. The main reason for dose reduction was the occurrence of adverse events (4.0%, n=58). Other reasons were: nonadherence (1.2%, n=18), organizational reasons (0.1%, n=2) and others (0.9%, n=13). 23.4% (n=15) of patients received at least one reduced carfilzomib dose during their course of treatment. The mean adherence to the carfilzomib dosing regimen (i.e., the percentage of doses administered as scheduled by the treating physician and not modified for adherence reasons) was 94.8%. Conclusion: According to our interim results, 86% of carfilzomib administrations were given in time and more than 90% of administrations were given at the recommended dose. Deviations from the recommended carfilzomib regimen were mainly due to safety issues or organizational reasons, but not due to nonadherence. Carfilzomib treatment adherence was almost 95%. Though, despite the required twice weekly dosing schedule, the carfilzomib regimen seems to be a convenient treatment option for multiple myeloma patients. Results have to be confirmed at final analysis. Disclosures Knauf: Celgene: Consultancy, Honoraria; Roche: Consultancy; Amgen: Consultancy, Honoraria; Mundipharma: Consultancy; Gilead Sciences: Consultancy; AbbVie: Consultancy; Janssen: Consultancy. Marschner:Amgen: Consultancy, Honoraria; IOMEDICO: Employment, Equity Ownership; Sandoz: Honoraria.

scholarly journals A retrospective observational study of intraductal breast papilloma and its coexisting lesions: a real-world experience

2019 ◽  
Author(s):  
Xiaoyun Mao ◽  
Huan Wang ◽  
Zhe Sun ◽  
Chuifeng Fan ◽  
Feng Jin
Keyword(s):  
Real World ◽  
Chinese Women ◽  
Nipple Discharge ◽  
Clinical Manifestations ◽  
Clinical Information ◽  
Intraductal Papilloma ◽  
Breast Mass ◽  
Benign Lesions ◽  
Palpable Mass ◽  
Palpable Breast

Abstract Background: Breast intraductal papilloma are a heterogeneous group. The aim of this study is to investigate the intraductal breast papilloma and its coexisting lesions retrospectively in real-world practice. Methods: We retrospectively identified 4450 intraductal breast papilloma and its coexisting lesions. Results: 18.36% coexisted with malignant lesions of the breast, 37.33% coexisted with atypia hyperplasia, 25.24% coexisted with benign lesions and only 19.10% coexisted without concomitant lesions. In addition, 36.80% of intraductal breast papilloma had nipple discharge, 51.46% had a palpable breast mass and 16.45% had both nipple discharge and a palpable breast mass. 28.18% experienced discomfort or were asymptomatic. Furthermore, 98.99% had ultrasound abnormalities, 53.06% had intraductal hypoechoic upon ultrasound. 31.89% had mammographic distortion, 14.45% had microcalcification upon mammography. Intraductal breast papilloma with malignancy had significant correlations with clinical manifestations. Conclusion: Coexisting malignancy was also related to ultrasound abnormality (BIRADS 4C and 5), mammographic distortion and microcalcification upon mammography but was not related to the intraductal hypoechoic upon ultrasound. Coexisting atypical hyperplasia correlated with nipple discharge but not palpable mass, mammographic distortion or intraductal hypoechoic upon ultrasound. The coexisting atypia hyperplasia was also related to abnormality upon ultrasound or microcalcification compared with the benign lesions. The intraductal papilloma coexists with malignancy or atypia hyperplasia accounted for more than 50%, the clinical information on papilloma and its coexisting lesions is nonspecific. We recommended surgical treatment for benign intraductal papillary lesions. Impact: The current study provides insight into the real-world pattern of intraductal papillomas and their coexisting lesions in a population of Chinese women.

scholarly journals Determinants of Prophylaxis Regimen Choice for Patients with Hemophilia Α Switching to Bay 81-8973: Real World Findings from the Taurus Non-Interventional Study

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 5023-5023
Author(s):  
Beng Fuh ◽  
Cristina Santoro ◽  
Philip Maes ◽  
Maria Eva Mingot-Castellano ◽  
Rubén Berrueco ◽  
...  
Keyword(s):  
Real World ◽  
Hemophilia A ◽  
Clinical Information ◽  
Patient Characteristics ◽  
Current Treatment ◽  
Activity Level ◽  
Real World Data ◽  
Open Label ◽  
Disease Characteristics ◽  
Bleeding History

Abstract BACKGROUND: Prophylaxis dosing regimens with standard half-life FVIII products range from 2-3 times per week to every other day regimens, and are adjusted according to patient needs. BAY 81-8973 (Kovaltry®, Bayer) is an unmodified full-length recombinant FVIII indicated for prophylaxis and treatment of bleeds in patients with hemophilia A; BAY 81-8973 was launched in 2016 and has since accumulated 6765 patient-years of exposure. The TAURUS study (NCT02830477) was established to investigate BAY 81-8973 prophylaxis use in clinical practice. OBJECTIVE: To report reasons for choosing dose regimens at the time of switching to BAY 81-8973 treatment, and patient and disease characteristics associated with choice of less frequent (≤ 2 times per week [≤ 2 xW]) versus more frequent (≥ 3xW) treatment. METHODS: TAURUS is an international, open label, prospective, non-interventional, single arm study with a target recruitment of 350 previously treated patients with haemophilia A of all ages with moderate or severe hemophilia A (≤ 5% FVIII:C) with ≥ 50 exposure days to any FVIII who have been recently switched to prophylaxis with BAY 81-8973. At baseline, physicians document clinical information including their reason for choosing a specific prophylaxis regimen. The full study will run until 2020. A scheduled interim analysis (30% of patients recruited) was conducted using a cut-off date of 2 July 2018 to investigate the determinants of choosing a specific regimen when initiating BAY 81-8973. RESULTS: At the cut-off date, 160 patients were enrolled: patient characteristics are shown in the table. For patients in the ≥ 3xW dosing category at baseline (n = 94, 59%), BAY 81-8973 regimens were: every day, n =2; 4xW, n= 2; every other day, n = 24; 3xW, n = 66. for patients dosed ≤ 2xW (n = 52, 33%) were: 2xW, n = 43; every 4th day, n = 1; 1.5xW, n = 1; 1xW, n = 7. Dosing regimen details were missing for 14 patients. Median patient age was 22 years. Pre-study, the majority of patients had been on prophylaxis (97%; 83% on rFVIII-FS). The most common reason for switching to BAY 81-8973 was 'physician decision' (in 79 patients, 49%). Most patients (79%) had been receiving BAY 81-8973 for less than 3 months prior to study entry. At baseline, ≥3xW patients were younger than ≤2xW patients (21.5 vs 27.0 years), had been on prophylaxis for a longer period pre-study (13 vs. 9 years), had severe haemophilia (88% vs. 79%), and more had a history of inhibitors (7% vs. 4%). The proportion of patients with ≥1 target joint and bleeding in the year prior to study was similar for both groups at baseline. The reasons for prescribing the specific dosing frequencies are shown in the table. 'Patient/caregiver preference' and 'bleeding history' were cited less frequently for ≤2xW patients, while 'current treatment regimen', 'adherence/compliance history', and 'activity level' were cited more frequently for ≤2xW patients vs ≥3xW patients. No recruited patients developed inhibitors with BAY 81-8973. CONCLUSIONS: These real-world data from 160 patients show patients treated more frequently (≥3xW) with BAY 81-8973 were younger and had a longer prophylaxis treatment history than those treated less frequently ≤2xW. Patient preference, bleeding history, and current regimen, were the most frequently cited reasons for choosing a specific BAY 81-8973 regimen. Taken together, the data indicate that BAY 81-8973 treatment may be successfully individualized according to patient need and disease characteristics. Disclosures Maes: Bayer: Honoraria. Rauchensteiner:Bayer: Employment. Wang:CSL Behring: Consultancy; Terumo BCT: Other: CPC Clinical Research; Bayer, Novo Nordisk, Octapharma, Genentech, HEMA Biologics, Shire, CSL Behring: Honoraria; Bayer, Bioverative, Novo Nordisk, Octapharma, Shire, Genentech, Biomarain, Pfizer, CSL Behring, HEMA Biologics, Daiichi Sankyo: Research Funding; Novo Nordisk: Consultancy; Bayer: Consultancy.

scholarly journals Assessment of deep neural networks for the diagnosis of benign and malignant skin neoplasms in comparison with dermatologists: A retrospective validation study

PLoS Medicine ◽  
2020 ◽  
Vol 17 (11) ◽  
pp. e1003381
Author(s):  
Seung Seog Han ◽  
Ik Jun Moon ◽  
Seong Hwan Kim ◽  
Jung-Im Na ◽  
Myoung Shin Kim ◽  
...  
Keyword(s):  
Neural Networks ◽  
Sensitivity And Specificity ◽  
Real World ◽  
Clinical Information ◽  
Skin Neoplasms ◽  
Validation Dataset ◽  
Clinical Impression ◽  
Clinical Images ◽  
Clinical Diagnoses ◽  
Attending Physicians

Background The diagnostic performance of convolutional neural networks (CNNs) for diagnosing several types of skin neoplasms has been demonstrated as comparable with that of dermatologists using clinical photography. However, the generalizability should be demonstrated using a large-scale external dataset that includes most types of skin neoplasms. In this study, the performance of a neural network algorithm was compared with that of dermatologists in both real-world practice and experimental settings. Methods and findings To demonstrate generalizability, the skin cancer detection algorithm (https://rcnn.modelderm.com) developed in our previous study was used without modification. We conducted a retrospective study with all single lesion biopsied cases (43 disorders; 40,331 clinical images from 10,426 cases: 1,222 malignant cases and 9,204 benign cases); mean age (standard deviation [SD], 52.1 [18.3]; 4,701 men [45.1%]) were obtained from the Department of Dermatology, Severance Hospital in Seoul, Korea between January 1, 2008 and March 31, 2019. Using the external validation dataset, the predictions of the algorithm were compared with the clinical diagnoses of 65 attending physicians who had recorded the clinical diagnoses with thorough examinations in real-world practice. In addition, the results obtained by the algorithm for the data of randomly selected batches of 30 patients were compared with those obtained by 44 dermatologists in experimental settings; the dermatologists were only provided with multiple images of each lesion, without clinical information. With regard to the determination of malignancy, the area under the curve (AUC) achieved by the algorithm was 0.863 (95% confidence interval [CI] 0.852–0.875), when unprocessed clinical photographs were used. The sensitivity and specificity of the algorithm at the predefined high-specificity threshold were 62.7% (95% CI 59.9–65.1) and 90.0% (95% CI 89.4–90.6), respectively. Furthermore, the sensitivity and specificity of the first clinical impression of 65 attending physicians were 70.2% and 95.6%, respectively, which were superior to those of the algorithm (McNemar test; p < 0.0001). The positive and negative predictive values of the algorithm were 45.4% (CI 43.7–47.3) and 94.8% (CI 94.4–95.2), respectively, whereas those of the first clinical impression were 68.1% and 96.0%, respectively. In the reader test conducted using images corresponding to batches of 30 patients, the sensitivity and specificity of the algorithm at the predefined threshold were 66.9% (95% CI 57.7–76.0) and 87.4% (95% CI 82.5–92.2), respectively. Furthermore, the sensitivity and specificity derived from the first impression of 44 of the participants were 65.8% (95% CI 55.7–75.9) and 85.7% (95% CI 82.4–88.9), respectively, which are values comparable with those of the algorithm (Wilcoxon signed-rank test; p = 0.607 and 0.097). Limitations of this study include the exclusive use of high-quality clinical photographs taken in hospitals and the lack of ethnic diversity in the study population. Conclusions Our algorithm could diagnose skin tumors with nearly the same accuracy as a dermatologist when the diagnosis was performed solely with photographs. However, as a result of limited data relevancy, the performance was inferior to that of actual medical examination. To achieve more accurate predictive diagnoses, clinical information should be integrated with imaging information.

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