The rate of tumor growth, g, as a biomarker for overall survival (OS) in prostate cancer (PC) in clinical trials as well as in real-world data from the Veterans Administration Medical Centers (VAMCs).

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 5074-5074
Author(s):  
Harshraj Leuva ◽  
Mengxi Zhou ◽  
Julia Wilkerson ◽  
Keith Sigel ◽  
Ta-Chueh Hsu ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Clinical Trial ◽  
Overall Survival ◽  
Clinical Trials ◽  
Tumor Growth ◽  
Real World ◽  
Clinical Trial Data ◽  
Trial Data ◽  
Real World Data ◽  
World Data

5074 Background: Novel assessments of efficacy are needed to improve determination of treatment outcomes in clinical trials and in real-world settings. Methods: Cancer treatments usually lead to concurrent regression and growth of the drug-sensitive and drug-resistant fractions of a tumor, respectively. We have exploited novel methods of analysis that assess these two simultaneous processes and have estimated rates of tumor growth ( g) and regression ( d) in over 30,000 patients (pts) with diverse tumors. Results: In prostate cancer (PC) we have analyzed both clinical trial and real-world data from Veterans. Using clinical trial data from 6819 pts enrolled in 15 treatment arms we have established separately and by combining all the data that g correlates highly (p<0.0001) with overall survival (OS) – slower g associated with better OS. In PC, abiraterone (ABI) and docetaxel (DOC) are superior to placebo, prednisone and mitoxantrone. ABI (median g =0.0017) is superior to DOC ( g=0.0021) in first line (p=0.0013); and ABI in 2nd line ( g=0.0034) is inferior to ABI in 1st line ( g=0.0017; p<0.0001). Finally, using combined clinical trial data as a benchmark we could assess the efficacy of novel therapies in as few as 30-40 patients. Amongst 7457 Veterans, the median g on a taxane ( g=0.0022) was similar to that from clinical trials ( g=0.0012). Although only 258 Veterans received cabazitaxel (CAB), g values for CAB ( g=0.0018) and DOC ( g=0.0023) were indistinguishable (p=0.3) consistent with their identical mechanism of action. Finally, outcomes with DOC in African American (AA) ( g=0.00212) and Caucasian ( g=0.00205) Veterans were indistinguishable (p=0.9) and comparable across all VAMCs. Conclusions: The rate of tumor growth, g, is an excellent biomarker for OS both in clinical trials and in real-world settings. g allows comparisons between trials and for large trial data sets to be used as benchmarks of efficacy. Real-world outcomes in the VAMCs are similar to those in clinical trials. In the egalitarian VAMCs DOC efficacy in PC is comparable in AA and Caucasian Veterans -- indicating inferior outcomes reported in AAs are likely due to differential health care access, not differences in biology.

scholarly journals Comparing SDTM and FHIR® for Real World Data from Electronic Health Records for Clinical Trial Submissions

2021 ◽  
Author(s):  
Sarah Riepenhausen ◽  
Cornelia Mertens ◽  
Martin Dugas
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Electronic Health Records ◽  
Real World ◽  
Clinical Trial Data ◽  
Trial Data ◽  
Real World Data ◽  
Health Records ◽  
World Data ◽  
Data Submission

Real world data for use in clinical trials is promising. We compared the SDTM for clinical trial data submission with FHIR® for routine documentation. After categorization of variables by relevance, clinically relevant SDTM items were mapped to FHIR®. About 30% in both were seen as clinically relevant. The majority of these SDTM items were mappable to FHIR® Observation resource.

Estimate of Real-World Medical Costs Avoidance When New Oral Anticoagulants Are Used Vs. Standard Therapy for the Treatment of Patients with Venous Thromboembolism in the U.S

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 687-687
Author(s):  
Alpesh N Amin ◽  
Amanda Bruno ◽  
Jeffrey Trocio ◽  
Jay Lin ◽  
Melissa Lingohr-Smith
Keyword(s):  
Clinical Trial ◽  
Medical Cost ◽  
Real World ◽  
Standard Therapy ◽  
Clinical Trial Data ◽  
Medical Costs ◽  
Trial Data ◽  
Real World Data ◽  
World Data ◽  
Event Rates

Abstract Introduction: Clinical trials have demonstrated that the new oral anticoagulants (NOACs), dabigatran, rivaroxaban, apixaban, and edoxaban are noninferior to standard therapies for treatment of acute symptomatic venous thromboembolism (VTE). We have previously published the medical costs avoided when NOACs are used instead of standard therapies based on rates of clinical events reported in clinical trials. However, the rates of recurrent VTE and major bleeding (MB) in the real-world settings may differ from those from the clinical trials. In this study, we estimated the real-world medical cost avoidance from a U.S. payer perspective when NOACs are used instead of standard therapy for the treatment of patients with VTE. Methods: Reduction of real-world event rates of recurrent VTE and MB were obtained by applying rate reductions observed in clinical studies to the Worcester population. Incremental annual medical costs among patients with VTE and MB from a U.S. payer perspective were obtained from the literature or healthcare claims databases and inflation adjusted to 2013 costs. Differences in total medical costs associated with clinical endpoints for patients treated with NOACs vs. standard therapy were then estimated. One-way univariate and Monte Carlo sensitivity analyses were additionally carried out. Univariate analysis varied the estimates of the clinical event rates between the ranges of confidence intervals and the estimates of event costs ±30% when such confidence intervals were not reported. Ten thousand cycles of Monte-Carlo simulations were used for additional sensitivity analysis where all model parameters were allowed to vary simultaneously. Results: Real-world event rates of recurrent VTE and MB in the Worcester VTE study were 11.2% and 10.8% respectively. Differences in real-world event rates of recurrent VTE among VTE patients treated with NOACs instead of standard therapy were estimated at -1.80% for apixaban, -1.23% for rivaroxaban, -2.02% for edoxaban, and 1.02% for dabigatran. Differences in real-world event rates of MB among VTE patients treated with NOACs instead of standard therapy were estimated at -7.48% for apixaban, -4.97% for rivaroxaban, -1.73% for edoxaban, and -2.57% for dabigatran. Based on the real-world data, the annual total medical cost avoidances vs. standard therapy were greatest for VTE patients treated with apixaban (-$4,440 per patient year-ppy), followed by those treated with rivaroxaban (-$2,971 ppy), edoxaban (-$1,957 ppy), and dabigatran (-$572 ppy). In comparison to data previously reported based on clinical trials, these medical cost avoidances are substantially greater for any of the NOACs vs. standard therapy (Table). The medical cost avoidances remained consistent under univariate (one-way) sensitivity. Additionally, the mean cost estimates of 10,000 random cycles of Monte-Carlo simulations for each of the NOACs were similar to the default estimated medical cost avoidances, demonstrating the robustness of the model estimates. Conclusions: Based on real-world data, when any of the evaluated NOACs are used instead of standard therapy for treatment of patients with acute VTE annual medical costs are reduced. In the real-world setting, the use of NOACs vs. standard therapy is predicted to be associated with even greater annual medical cost reductions than that previously estimated based on clinical trial data. Of the NOACs, apixaban has the greatest real-world medical cost avoidance, as its use is associated with substantial reductions in both VTE and MB event rates. Abstract 687. Table 1 Estimates of Medical Cost Differences Among VTE Patients Treated with NOACs vs. Standard Therapy Based on Clinical Trial Data vs. Real-World Data Outcome Apixaban ($/patient-yr) Rivaroxaban ($/patient-yr) Edoxaban ($/patient-yr) Dabigatran ($/patient-yr) Recurrent VTE* Clinical trial data -$252 -$132 -$197 $114 Real-world data -$1,047 -$717 -$1,173 $595 Major bleedings* Clinical trial data -$572 -$354 -$109 -$195 Real-world data -$3,392 -$2,254 -$784 -$1,167 Total Medical Cost* Clinical trial data -$824 -$486 -$306 -$80 Real-world data -$4,440 -$2,971 -$1,957 -$572 *Negative values mean the NOAC is associated with lower total medical cost vs. standard therapy. Disclosures Amin: Bristol-Myers Squibb, Pfizer: Consultancy. Off Label Use: Apixaban and edoxaban for the indication of VTE. Bruno:Bristol-Myers Squibb: Employment, Equity Ownership. Trocio:Pfizer: Employment, Equity Ownership. Lin:Bristol-Myers Squibb, Pfizer: Consultancy, Research Funding. Lingohr-Smith:Bristol-Myers Squibb, Pfizer: Consultancy, Research Funding.

PP81 Real World Data: The Early Access To Medicines Scheme Catches The Worm

2019 ◽  
Vol 35 (S1) ◽  
pp. 53-53
Author(s):  
Adam Hall ◽  
Lok Wan Liu ◽  
Richard Macaulay ◽  
Sean Walsh
Keyword(s):  
Clinical Trial ◽  
Clinical Practice ◽  
Real World ◽  
Clinical Trial Data ◽  
Access To Medicines ◽  
Trial Data ◽  
Real World Data ◽  
World Data ◽  
Early Access ◽  
Nice Guidance

IntroductionThe Early Access to Medicines Scheme (EAMS) aims to provide access to medicines prior to market authorization for patients with severe, life-threatening diseases who do not have adequate treatment options. An EAMS designation enables the potential collection of United Kingdom-specific real world evidence (RWE) prior to health technology assessment (HTA) by the National Institute for Health and Care Excellence (NICE). This research evaluates whether RWE is being gathered through the EAMS and utilized to support HTA submissions.MethodsAll EAMS designations as of 7 November 2018 were identified from the Medicines and Healthcare products Regulatory Agency website. For products with final NICE guidance, all publicly-available NICE documentation was reviewed.ResultsSixteen product and indication pairings with an EAMS designation were identified, with 12 having received final NICE guidance (11 were recommended, 3 were recommended for temporary reimbursement via the Cancer Drugs Fund, and 2 were not recommended). Of the 11 recommended products, seven had references to the number of patients or sites with product access through the EAMS, but only one (dupilumab for atopic dermatitis) had detailed data collected during the EAMS period. The manufacturer of dupilumab reported baseline demographics and disease characteristics from a cohort of 35 patients treated under the EAMS to inform the generalizability of trial populations for clinical practice. Follow-up results from this cohort demonstrated that real-world data on dupilumab effectiveness was comparable with the clinical trial data, despite a higher proportion of patients in the real-world cohort receiving immunosuppressant therapy, which makes improvements in efficacy harder to achieve. The committee also noted that the RWE presented supported the understanding of dupilumab's long-term clinical effectiveness and informed assumptions for the economic model.ConclusionsTo date, the majority of products receiving an EAMS designation have not presented RWE at NICE reappraisal. The case of dupilumab illustrated how RWE collected through the EAMS can be used to reduce uncertainty around how clinical trial data can be translated into clinical practice. In the future, RWE may increasingly be used to help inform NICE decisions.

scholarly journals The impact of patient-reported outcome (PRO) data from clinical trials: a systematic review and critical analysis

2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Samantha Cruz Rivera ◽  
Derek G. Kyte ◽  
Olalekan Lee Aiyegbusi ◽  
Anita L. Slade ◽  
Christel McMullan ◽  
...  
Keyword(s):  
Systematic Review ◽  
Clinical Trial ◽  
Clinical Trials ◽  
Case Studies ◽  
Real World ◽  
Clinical Trial Data ◽  
Research Impact ◽  
Trial Data ◽  
Patient Reported ◽  
The Impact

Abstract Background Patient-reported outcomes (PROs) are commonly collected in clinical trials and should provide impactful evidence on the effect of interventions on patient symptoms and quality of life. However, it is unclear how PRO impact is currently realised in practice. In addition, the different types of impact associated with PRO trial results, their barriers and facilitators, and appropriate impact metrics are not well defined. Therefore, our objectives were: i) to determine the range of potential impacts from PRO clinical trial data, ii) identify potential PRO impact metrics and iii) identify barriers/facilitators to maximising PRO impact; and iv) to examine real-world evidence of PRO trial data impact based on Research Excellence Framework (REF) impact case studies. Methods Two independent investigators searched MEDLINE, EMBASE, CINAHL+, HMIC databases from inception until December 2018. Articles were eligible if they discussed research impact in the context of PRO clinical trial data. In addition, the REF 2014 database was systematically searched. REF impact case studies were included if they incorporated PRO data in a clinical trial. Results Thirty-nine publications of eleven thousand four hundred eighty screened met the inclusion criteria. Nine types of PRO trial impact were identified; the most frequent of which centred around PRO data informing clinical decision-making. The included publications identified several barriers and facilitators around PRO trial design, conduct, analysis and report that can hinder or promote the impact of PRO trial data. Sixty-nine out of two hundred nine screened REF 2014 case studies were included. 12 (17%) REF case studies led to demonstrable impact including changes to international guidelines; national guidelines; influencing cost-effectiveness analysis; and influencing drug approvals. Conclusions PRO trial data may potentially lead to a range of benefits for patients and society, which can be measured through appropriate impact metrics. However, in practice there is relatively limited evidence demonstrating directly attributable and indirect real world PRO-related research impact. In part, this is due to the wider challenges of measuring the impact of research and PRO-specific issues around design, conduct, analysis and reporting. Adherence to guidelines and multi-stakeholder collaboration is essential to maximise the use of PRO trial data, facilitate impact and minimise research waste. Trial registration Systematic Review registration PROSPERO CRD42017067799.

Tumor response and growth rate of nivolumab treatment in advanced gastric cancer: Real-world data from a large observational/translational study, JACCRO GC-08 (deliver trial).

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 4527-4527
Author(s):  
Ryohei Kawabata ◽  
Yasuhiro Sakamoto ◽  
Eisuke Inoue ◽  
Atsushi Ishiguro ◽  
Yusuke Akamaru ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Clinical Trial ◽  
Growth Rate ◽  
Tumor Growth ◽  
Real World ◽  
Fold Increase ◽  
Real World Data ◽  
World Data ◽  
Translational Study ◽  
Before And After

4527 Background: Nivolumab (Nivo) demonstrated survival benefit in previously treated gastric cancer (GC) patients (pts), with a response rate (RR) of 11% and a disease control rate (DCR) of 40% (Kang YK, et al. Lancet 2017). There are few real-world data of Nivo and its predictive markers are needed in GC. It has been demonstrated that some tumors grow rapidly after Nivo treatment, but the proportion is uncertain. Methods: DELIVER trial was a prospective, multicenter, observational/translational study which assessed pts with advanced GC treated with Nivo alone and ECOG Performance Status (PS) 0-2 (UMIN000030850). The aims were to evaluate the efficacy and safety of Nivo in real world, and to discover novel host-related immune-biomarkers (gut microbiome, genetic polymorphism, gene expression, and metabolome) using fecal and blood samples which were collected before and after Nivo treatment. The RR, DCR, progression-free survival, overall survival, and tumor growth rate (TGR) were estimated as the efficacy. The response was evaluated by first imaging based on RECIST version 1.1. The TGR was calculated as a percentage increase in tumor volume during 1 month (Champiat et al. Clin Cancer Res 2017). Results: A total of 501 pts was enrolled in this study from Mar 2018 to Aug 2019, and 487 pts were evaluable for analysis (median age 70-y, 71% male, ECOG PS0/1/2 42%/44%/14%, tub/por/sig 45%/41%/5%, 21% HER2-pos, 42% pts with ascites). The DCR was 39.2% (95%CI 34.9-43.7) in evaluable pts. In 282 pts with measurable lesions, the RR was 6.7% (95%CI 4.1-10.3) and DCR was 36.5%. Sub-analysis by patient background indicated that DCR was 41% for PS0, 42% for PS1, and 24% for PS2. In addition, the DCR was lower in pts with ascites compared to those without ascites (28.6% vs. 47.0%, p= 0.005). The TGR decreased after introduction of Nivo in 124 (56.6%) of 219 evaluable pts for TGR; however, 20.5% pts were identified as experiencing hyper-progressive disease (HPD) which was defined as a ≥2-fold increase of the TGR before and after Nivo. When defining HPD as a ≥2-fold increase of tumor growth kinetics ratio and 50% increase of tumor burden, 9.6% pts experienced it. Conclusions: The real-word data of the large observational trial showed a comparable DCR to that of clinical trial in advanced GC treated with Nivo. This trial revealed the tumor behavior and some pts who experienced rapid tumor growth after Nivo treatment in clinical practice; biomarkers for HPD and the definition should be established. Clinical trial information: UMIN000030850 .

A retrospective analysis of treatment patterns in metastatic castration-resistant prostate cancer patients treated with radium-223.

2019 ◽  
Vol 37 (7_suppl) ◽  
pp. 180-180 ◽  
Author(s):  
A. Oliver Sartor ◽  
Sreevalsa Appukkuttan ◽  
Ronald E. Aubert ◽  
Jeffrey Weiss ◽  
Joy Wang ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Real World ◽  
Pilot Trial ◽  
Clinical Trial Data ◽  
Castration Resistant Prostate Cancer ◽  
Real World Data ◽  
Data Set ◽  
World Data ◽  
Castration Resistant ◽  
Radium 223

180 Background: Radium-223 (RA-223) is the first FDA approved targeted alpha therapy that significantly improves overall survival (OS) in patients (pts) with metastatic castration resistant prostate cancer (mCRPC) with symptomatic bone metastases. There is limited real world data describing RA-223 current use. Methods: A retrospective patient chart review was done of men who received at least 1 cycle of Ra-223 for mCRPC in 10 centers throughout the US (4 academic, 6 private practices). All pts had a minimum follow-up of 4 months, or placed in hospice or death. Descriptive analyses for clinical characteristics and treatment outcomes were performed. Results: Among the 200 pts (mean age-73.6 years, mean Charlson comorbidity index-6.9) RA-223 was initiated on average 1.6 years from mCRPC diagnosis (first line use (1L)=38.5%, 2L=31.5% and ≥3L=30%). 78% completed 5-6 cycles of RA-223 with mean therapy duration of 4.2 months. Among all pts, 43% received RA-223 as monotherapy (no overlap with other mCRPC therapies) while 57% had combination therapy with either abiraterone or enzalutamide. Median OS following RA-223 initiation was 21.2 months (95% CI 19.6- 29.2). Table provides the RA-223 utilization by type of clinical practice. Conclusions: Utilization of RA-223 in this real world data set was distinct from clinical trial data. Most patients received RA-223 in combination with abiraterone or enzalutamide, therapies that were unavailable when the pilot trial was conducted. Median survival was 21.2 months. Real world use of RA-223 has evolved as newer agents have become FDA approved in bone-metastatic CRPC. Academic and community patterns of practice were more similar than distinct. [Table: see text]

A methodology for the extraction and analysis of real-world radiographic and electronic medical record data to reconstruct treatment arms of historical prostate cancer clinical trials.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 5033-5033
Author(s):  
William David Lindsay ◽  
Christopher A. Ahern ◽  
Aaron Kamauu ◽  
Robert Wilder ◽  
Karen Chagin ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Clinical Trial ◽  
Clinical Trials ◽  
Real World ◽  
Castration Resistant Prostate Cancer ◽  
Efficacy Evaluation ◽  
Real World Data ◽  
Trial Treatment ◽  
Picture Archiving And Communication

5033 Background: Real-world evidence (RWE), including synthetic comparator arms created from historical real-world data (RWD), has the potential to support the safety and efficacy evaluation of new medical products. However, many available RWD sources lack the details necessary to reliably identify patients comparable to clinical trial cohorts or to assess essential oncologic efficacy endpoints. This project demonstrates the ability to extract and analyze RWD to identify patients matching eligibility criteria to four historical clinical trials in metastatic castration-resistant prostate cancer (mCRPC), and calculate outcome measures. Methods: A total of 5,741 patients treated for prostate cancer at multiple institutions (2010-2020) were analyzed in two cohorts using data extracted from the EMR, Tumor Registry, Oncology Information System, and Picture Archiving and Communication System. Of 3,486 patients with prostate cancer in Cohort 1, 422 mCRPC patients were identified: those treated with ADT who achieved castration-level testosterone ( < 50 ng/dL), had evidence of metastatic disease, and exhibited rising PSA (PCWG2). These patients were further matched to four historical clinical trial treatment arms (COU-AA-301: 49, COU-AA-302: 143, AFFIRM: 30, PREVAIL: 79), based on prior chemotherapy and receipt of Abiraterone or Enzalutamide. Overall survival (OS) and time to skeletal related events (SRE) (pathological fracture, spinal compression, surgery to bone, and radiotherapy to bone) were calculated based on diagnosis and procedure codes using the Kaplan-Meier (KM) Estimator. Of 2,255 patients with prostate cancer in Cohort 2, 101 patients received Abiraterone or Enzalutamide and 59 patients had sufficient baseline and follow-up imaging to be scored. Radiographic progression-free survival (rPFS) was calculated from the start of treatment to the time of progression (RECIST 1.1) or loss to follow-up using the KM estimator. Results: In Cohort 1, median OS was 37.7 months (95% CI: 31.5-NR), and median time to SRE was 17.9 months (13.5-22.6). Median OS per patient cohort matched to historical trial treatment arm was COU-AA-301: 23.7 months (10.7-NR), COU-AA-302: 45.9 months (34.9-NR), AFFIRM: 35.3 months (6.34-NR), PREVAIL: 41.5 months (21.9-NR). In Cohort 2, median rPFS was 37.2 months (13.3-NR). Conclusions: The methodology employed in this analysis not only successfully identified a cohort of RWD patients similar to clinical trial-defined patients, but also curated sufficiently reliable data to calculate essential endpoints (e.g., rPFS). At scale, this methodology can be used to generate RWE, including synthetic comparator arms to support clinical trials with radiographic endpoints.

scholarly journals Machine learning enabled subgroup analysis with real-world data to inform better clinical trial design

2021 ◽  
Author(s):  
Jie Xu ◽  
Hao Zhang ◽  
Hansi Zhang ◽  
Jiang Bian ◽  
Fei Wang
Keyword(s):  
Machine Learning ◽  
Clinical Trial ◽  
Clinical Trials ◽  
Real World ◽  
Clinical Manifestations ◽  
Research Network ◽  
Real World Data ◽  
Eligibility Criteria ◽  
World Data ◽  
Patient Subgroups

Restrictive eligibility criteria for clinical trials may limit the generalizability of treatment effectiveness and safety to real-world patients. In this paper, we propose a machine learning approach to derive patient subgroups from real-world data (RWD), such that the patients within the same subgroup share similar clinical characteristics and safety outcomes. The effectiveness of our approach was validated on two existing clinical trials with the electronic health records (EHRs) from a large clinical research network. One is the donepezil trial for Alzheimer's disease (AD), and the other is the Bevacizumab trial on colon cancer (CRC). The results show that our proposed algorithm can identify patient subgroups with coherent clinical manifestations and similar risk levels of encountering severe adverse events (SAEs). We further exemplify that potential rules for describing the patient subgroups with less SAEs can be derived to inform the design of clinical trial eligibility criteria.

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