scholarly journals Transfusion Independence in Lower-Risk, Non-del5(q) Myelodysplastic Syndromes (LR-MDS) Among Patients (pts) Initiating Hypomethylating Agents (HMAs) While Receiving Red Blood Cell (RBC) Transfusions

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 838-838 ◽  
Author(s):  
Amer M. Zeidan ◽  
Weiwei Zhu ◽  
Rong Wang ◽  
Maximilian Stahl ◽  
Scott F Huntington ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Median Time ◽  
Research Funding ◽  
Cox Model ◽  
Clinical Trial Data ◽  
Trial Data ◽  
Lower Probability ◽  
Medicare Claims ◽  
Transfusion Independence ◽  
Significant Difference

Abstract Background: HMAs were approved in the U.S. for treatment of MDS in 2004 (azacitidine) and 2006 (decitabine), and are used for upfront management higher risk disease and in LR-MDS at progression or after failure or low likelihood to respond to erythropoiesis stimulating agents (ESAs). Clinical trial data suggest that 24-50% of LR-MDS pts achieve RBC transfusion independence (TI) from prior transfusion dependence (TD) with HMA therapy. Response among older pts with LR-MDS treated with HMA in a real-world setting is unclear. We have previously shown that survival of higher risk MDS pts treated with HMAs in real-life setting is much shorter than clinical trial data. We therefore examined rates of achieving TI in LR-MDS pts receiving HMAs. Methods: We identified adults >65 years old diagnosed with LR-MDS (WHO categories RA, RARS, and RCMD) in 2004-2013 from the Surveillance Epidemiology and End Results Medicare claims data. Exclusion criteria include: pts with MDS diagnosed on autopsy report or death certificate, absence of continuous Medicare Part A and B coverage or presence of HMO enrollment from 12 months prior to diagnosis through death or end of study (12/31/2014). Pts had to initiate at least one cycle of HMA, defined as 3 to 10 doses of HMA within 28 days. A gap in treatment between 14 to 28 days indicates a new cycle. Pts were assessed for their transfusion status each week throughout the study period. We measured weekly transfusion status based on receipt of RBC transfusions (observed in Medicare claims) during the current and prior 7 weeks (8 weeks total). Transfusion status was defined as: transfusion receiving (TR), pts received at least one transfusion in each period; TD, patient received ≥2 transfusions over 8 weeks, with ≥2 transfusions ≥2 weeks apart; TI, no transfusions within the 8-week period. We required pts to be at least TR at HMA initiation. We censored observations one month prior to death and 4 weeks after the end of the last HMA cycle. TI duration is defined as number of weeks between last transfusion before achieving TI and first transfusion after TI. TI ends the week that the pt receives a transfusion. Time to achieve TI as well as duration of TI were assessed with Kaplan-Meier and Cox models, adjusting for patient's demographics, health status at HMA initiation, prior hospitalization for bleeding and infection, and prior erythropoiesis-stimulating agent and transfusion use. Analysis was also conducted among the subset of pts who were TD at time of first HMA. Results: Among 336 pts with LR-MDS who initiated HMA while RBC TR, median age was 76 years (interquartile range [IQR]: 71-81) and 87.2% were non-Hispanic white. Median time to HMA initiation from diagnosis of MDS was 44.3 (IQR: 13-117) weeks. 136 (40.5%) pts achieved RBC TI, with median time of 23 (95% confidence interval [CI]: 18-28) weeks (Figure 1a). Multivariate Cox model showed pts receiving ≥3 transfusions in the 8 weeks before HMA initiation were less likely to achieve TI (HR: 0.46, p<.01). Geographic region of residence also affected time to TI, with pts in the Northeast and West having lower probability of achieving TI compared to pts in the Midwest (hazard ratio [HR]: 0.44, 95% CI: 0.24-0.80 and HR: 0.56, 0.36-0.87 respectively). Medicaid dual coverage also had a positive association with achieving TI (HR: 1.92, p=.03). Median TI duration was 50 (95% CI:26-76) weeks (Figure 1b). Among 192 pts who were TD at HMA initiation, 64 (33.3%) achieved TI, with a median time to TI of 32 (95% CI: 24-71) weeks. Median TI duration was 60 (95% CI: 23-87) weeks. TD pts of older age (>85 years) showed a higher tendency of losing TI over younger pts (age 66-69) (HR: 4.50, p=.04). Conclusions: Achieving TI is an important quality of life outcome for MDS pts. Our results indicate that a substantial portion of HMA recipients who were RBC TD or TR at initiation achieved TI status, with slightly shorter time to achieve TI for those who initiated while TR compared to TD, and no significant difference in duration of TI. Our results are limited by inability to assess for lenalidomide use and lack of ascertainment of reason of HMA initiation (progression of LR-MDS versus ESA failure). Observed rates of achieving RBC TI in LR-MDS pts utilizing HMA were consistent with clinical trials. Disclosures Zeidan: Celgene: Consultancy; Gilead: Consultancy; Pfizer: Consultancy; Incyte: Employment; Abbvie: Consultancy; Ariad: Consultancy, Speakers Bureau; Agios: Consultancy; Novartis: Consultancy. Huntington:Celgene: Consultancy; Bayer: Consultancy; Janssen: Consultancy. Podoltsev:Pfizer: Membership on an entity's Board of Directors or advisory committees; Sunesis Pharmaceuticals: Research Funding; Pfizer: Research Funding; Celator: Research Funding; Astellas Pharma: Research Funding; Astex Pharmaceuticals: Research Funding; Celgene: Research Funding; Genentech: Research Funding; LAM Therapeutics: Research Funding; Daiichi Snakyo: Research Funding; Boehringer Ingelheim: Research Funding. Gore:Celgene: Consultancy, Research Funding. Ma:Celgene: Consultancy; Incyte: Consultancy. Davidoff:Celgene: Research Funding.

scholarly journals Using Administrative Data to Identify Relapse and Hematopoietic Stem Cell Transplantation (HSCT) in Children with Acute Lymphoblastic Leukemia (ALL): Validation at Two Centers and Incidence Estimation in a National Cohort

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 624-624
Author(s):  
Viviane C. Cahen ◽  
Yimei Li ◽  
Caitlin W Elgarten ◽  
Amanda M. DiNofia ◽  
Jennifer J. Wilkes ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Administrative Data ◽  
Gold Standard ◽  
Research Funding ◽  
Clinical Trial Data ◽  
Trial Data ◽  
National Cohort ◽  
Data Source ◽  
Procedure Codes

Abstract Administrative databases can be used to study outcomes including patients outside of clinical trials and have been used to identify relapse and HSCT in adult and adolescent/young adult leukemia populations. However, there are no published studies using validated billing and diagnostic codes to identify timing of relapse or HSCT in children with ALL. Published approaches are limited to relapses occurring after cessation of therapy, but a substantial proportion of pediatric ALL relapses occur on therapy. We hypothesized HSCT and early and late relapses could be detected accurately in a previously assembled cohort of children with ALL (Fisher 2014 Med Care), using pharmacy billing and ICD-9 diagnosis and procedure codes. We present our methods, validated at two large freestanding children's hospitals, and incidence estimates of relapse or HSCT as first events in a national cohort. The Pediatric Health Information System (PHIS) cohort included patients aged 0-21 admitted between 1/1/2004 and 12/13/2013, previously identified with de novo ALL. We reviewed daily inpatient pharmacy, diagnosis, and procedure codes for patients in the PHIS ALL cohort from the Children's Hospital of Philadelphia (CHOP; 2004-2013) and Texas Children's Hospital (TCH; 2007-2013). Events were captured until the first of 5 years from diagnosis or last day of PHIS data. Relapses were identified using ICD-9 diagnosis/procedure codes and PHIS pharmacy codes (Figure 1A) correlating with relapse regimens. Manual review of daily PHIS data was performed for second-line chemotherapy at any time, reinduction-style chemotherapy365 days after diagnosis, or a relapsed ALL ICD-9 diagnosis code (204.02). HSCTs were identified using ICD-9 procedure and PHIS pharmacy code patterns consistent with conditioning (Figure 1B). We reviewed electronic medical records (EMR) for patients with do novo ALL from CHOP and TCH for all relapses and HSCTs as the gold standard. Demographics were evaluated by hospital and data source using chi-square tests. We calculated sensitivity and positive-predictive value (PPV) of PHIS-defined events compared to the EMR gold standard at the patient level and only considered the first relapse and HSCT per patient. PHIS events were considered valid if the date was within ±14 days of the EMR. We estimated 5-year incidences of relapse and HSCT as first events for the entire PHIS cohort, infants (<1 year at diagnosis), and high-risk ALL (receipt of daunorubicin in Induction). Of 395 patients in the CHOP EMR cohort, 362 matched with the PHIS ALL cohort. The TCH EMR cohort had 410 patients, matching 329 from PHIS. Age, sex, and Down syndrome were similar (Table 1). CHOP patients were more likely to be Black, and race distribution within each hospital was similar by data source. Fewer CHOP patients were Hispanic, and more had missing ethnicity. Fewer TCH patients were missing ethnicity regardless of data source, though PHIS had a higher proportion of missing data. Proportions of children with high- and low-risk B-ALL, T-ALL, infant ALL, and Induction daunorubicin were similar. Government primary insurance in the first admission was more common at TCH. At CHOP, 39 relapses were identified in PHIS, and 45 by EMR (sensitivity 85.7%, PPV 100%). At TCH, 30/31 relapses were correctly identified in PHIS (sensitivity 96.6%, PPV 100%). Our PHIS algorithm identified 38 CHOP patients who underwent HSCT during the study period and 34 at TCH. All matched the EMR, with 100% sensitivity and PPV for both hospitals. Table 2 shows five-year incidences of relapse and HSCT in the entire PHIS ALL cohort (N=10,162), including relapse estimates adjusted for sensitivity. Relapses and HSCTs were higher in infants and in children receiving daunorubicin. We present novel approaches to identify relapse and HSCT events using administrative data, validated at two children's hospitals. Timing of events are matched within ±14 days. Relapse estimates are slightly lower than clinical trial data, but this approach has higher sensitivity than published administrative data reports, and sensitivity-adjusted rates approximate clinical trial data. Detected events are likely to be true based on the 100% PPV. Our relapse identification approach is complex and requires disease-specific clinical expertise to identify relapse-style chemotherapy patterns in children on therapy; however, this approach can capture early relapses in children outside of clinical trials. Disclosures Fisher: Merck: Research Funding; Pfizer: Research Funding.

Clinical Trial Data Management Software: A Review of the Technical Features

2019 ◽  
Vol 14 (3) ◽  
pp. 160-172 ◽  
Author(s):  
Aynaz Nourani ◽  
Haleh Ayatollahi ◽  
Masoud Solaymani Dodaran
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Data Management ◽  
Clinical Data ◽  
Clinical Trial Data ◽  
Trial Data ◽  
Data Management System ◽  
Management Systems ◽  
Data Management Systems ◽  
Technical Features

Background:Data management is an important, complex and multidimensional process in clinical trials. The execution of this process is very difficult and expensive without the use of information technology. A clinical data management system is software that is vastly used for managing the data generated in clinical trials. The objective of this study was to review the technical features of clinical trial data management systems.Methods:Related articles were identified by searching databases, such as Web of Science, Scopus, Science Direct, ProQuest, Ovid and PubMed. All of the research papers related to clinical data management systems which were published between 2007 and 2017 (n=19) were included in the study.Results:Most of the clinical data management systems were web-based systems developed based on the needs of a specific clinical trial in the shortest possible time. The SQL Server and MySQL databases were used in the development of the systems. These systems did not fully support the process of clinical data management. In addition, most of the systems lacked flexibility and extensibility for system development.Conclusion:It seems that most of the systems used in the research centers were weak in terms of supporting the process of data management and managing clinical trial's workflow. Therefore, more attention should be paid to design a more complete, usable, and high quality data management system for clinical trials. More studies are suggested to identify the features of the successful systems used in clinical trials.

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