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Background The understanding of the impact of COVID‐19 in patients with cancer is evolving, with need for rapid analysis. Aims This study aims to compare the clinical and demographic characteristics of patients with cancer (with and without COVID‐19) and characterize the clinical outcomes of patients with COVID‐19 and cancer. Methods and Results Real‐world data (RWD) from two health systems were used to identify 146 702 adults diagnosed with cancer between 2015 and 2020; 1267 COVID‐19 cases were identified between February 1 and July 30, 2020. Demographic, clinical, and socioeconomic characteristics were extracted. Incidence of all‐cause mortality, hospitalizations, and invasive respiratory support was assessed between February 1 and August 14, 2020. Among patients with cancer, patients with COVID‐19 were more likely to be Non‐Hispanic black (NHB), have active cancer, have comorbidities, and/or live in zip codes with median household income

Data silos are proliferating while research and development activity explode following genetic and immunological advances for many clinically described disorders with previously unknown etiologies. The latter event has inspired optimism in the patient, clinical, and research communities that disease-specific treatments are on the way. However, we fear the tendency of various stakeholders to balkanize databases in proprietary formats, driven by current economic and academic incentives, will inevitably fragment the expanding knowledge base and undermine current and future research efforts to develop much-needed treatments. The proliferation of proprietary databases, compounded by a paucity of meaningful outcome measures and/or good natural history data, slows our ability to generate scalable solutions to benefit chronically underserved patient populations in ways that would translate to more common diseases. The current research and development landscape sets too many projects up for unnecessary failure, particularly in the rare disease sphere, and does a grave disservice to highly vulnerable patients. This system also encourages the collection of redundant data in uncoordinated parallel studies and registries to ultimately delay or deny potential treatments for ostensibly tractable diseases; it also promotes the waste of precious time, energy, and resources. Groups at the National Institutes of Health and Food and Drug Administration have started programs to address these issues. However, we and many others feel there should be significantly more discussion of how to coordinate and scale registry efforts. Such discourse aims to reduce needless complexity and duplication of efforts, as well as promote a pre-competitive knowledge ecosystem for rare disease drug development that cultivates and accelerates innovation.

Introduction: Reports suggest worsened outcomes in patients with cancer (pts) and COVID-19 (Cov), varying by geography and local peak dynamics. We describe characteristics and clinical outcomes of pts with and without Cov. Methods: RWD at 2 Midwestern health systems from the Syapse Learning Health Network were used to identify adults with active cancer (AC) or past history of cancer (PHC). AC pts were identified by encounters with ICD-10 code for malignant neoplasm or receipt of an anticancer agent within 12 months prior to February 15, 2020; PHC pts were identified by encounters with an active cancer code from May 15, 2015 to February 15, 2019 and no receipt of anticancer therapy within the prior 12 months. Cov was defined by diagnostic codes and laboratory results from February 15 to May 13, 2020. Comorbidities were assessed prior to February 15, 2020; hospitalizations (hosp), invasive mechanical ventilation (IMV), and all-cause mortality (M) were assessed from February 15 to May 27, 2020. Results: We identified 800 pts with Cov (0.5%) out of a total of 154,585 pts with AC or PHC. Compared to AC pts without Cov (AC WO, 39,402), AC pts with Cov (AC Cov, 388) were more likely to be non-Hispanic Black (NHB, 39% vs. 9%), have renal failure (RF, 24% vs. 12%), cardiac arrhythmias (33% vs. 19%), congestive heart failure (CHF, 16% vs. 8%), obesity (19% vs. 14%), pulmonary circulation disorder (PCD, 9% vs. 4%), and a zip code with median annual household income (ZMI) Conclusion: In this rapid characterization from RWD, pts with Cov have higher rates of pre-existing cardiopulmonary/vascular and renal conditions and increased risk of hospitalization, IMV, and mortality than pts without Cov. Higher Cov risk and worse outcomes in NHB and lower-income pts suggest health care disparities. Whether these outcomes are due to comorbidities or acute sequelae merits further study, as does investigation of alternative definitions for real-world populations and outcomes. Citation Format: Shirish M. Gadgeel, Michael A. Thompson, Monika A. Izano, Clara Hwang, Tom Mikkelsen, James L. Weese, Frank M. Wolf, Andrew Schrag, Sheetal Walters, Harpreet Singh, Jonathan Hirsch, Thomas D. Brown, Paul G. Kluetz. Using real-world data (RWD) from an integrated platform for rapid analysis of patients with cancer with and without COVID-19 across distinct health systems [abstract]. In: Proceedings of the AACR Virtual Meeting: COVID-19 and Cancer; 2020 Jul 20-22. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(18_Suppl):Abstract nr S10-02.

The antibiotic resistance profile of Helicobacter pylori (H. pylori) is constantly changing. Up-to-date and reliable data for the effectiveness of first-line H. pylori treatment protocols are necessary to provide evidence-based best-practice guidelines.To determine the effectiveness, compliance and safety of first-line treatment for H. pylori in Israel.An observational, prospective, multicenter study was conducted in tertiary referral centers in Israel, as part of the European registry on H. pylori management (Hp-EuReg). H. pylori-infected patients were included from 2013 to March 2020. Data collected included demographics, clinical data, diagnostic tests, previous eradication attempts, current treatment, compliance, adverse events, and treatment outcome result.In total, 242 patients were registered, including 121 (50%) who received first-line therapy, 41% of these individuals received clarithromycin based triple therapy and 58.9% received a four-drug regimen. The overall effectiveness of first-line therapy was 85% and 86% by modified intention-to-treat and per protocol analyses, respectively. The effectiveness of both sequential and concomitant therapies was 100% while clarithromycin-based triple therapy achieved an eradication rate of 79%. Treatment eradication was higher among patients who received high dose proton pump inhibitor (PPI) compared to those treated with low dose PPI (100% vs. 81.5% respectively, P0.01). No difference in treatment effectiveness was found between 7-, 10-, and 14-day treatment.The effectiveness of clarithromycin-based triple therapy is suboptimal. First-line treatment of H. pylori infection should consist of four drugs, including high dose PPI, according to international guidelines.

Background The COVID-19 pandemic remains a significant global threat. However, despite urgent need, there remains uncertainty surrounding best practices for pharmaceutical interventions to treat COVID-19. In particular, conflicting evidence has emerged surrounding the use of hydroxychloroquine and azithromycin, alone or in combination, for COVID-19. The COVID-19 Evidence Accelerator convened by the Reagan-Udall Foundation for the FDA, in collaboration with Friends of Cancer Research, assembled experts from the health systems research, regulatory science, data science, and epidemiology to participate in a large parallel analysis of different data sets to further explore the effectiveness of these treatments. Methods Electronic health record (EHR) and claims data were extracted from seven separate databases. Parallel analyses were undertaken on data extracted from each source. Each analysis examined time to mortality in hospitalized patients treated with hydroxychloroquine, azithromycin, and the two in combination as compared to patients not treated with either drug. Cox proportional hazards models were used, and propensity score methods were undertaken to adjust for confounding. Frequencies of adverse events in each treatment group were also examined. Results Neither hydroxychloroquine nor azithromycin, alone or in combination, were significantly associated with time to mortality among hospitalized COVID-19 patients. No treatment groups appeared to have an elevated risk of adverse events. Conclusion Administration of hydroxychloroquine, azithromycin, and their combination appeared to have no effect on time to mortality in hospitalized COVID-19 patients. Continued research is needed to clarify best practices surrounding treatment of COVID-19.

Background: Pneumonitis (Pn) is a potentially life-threatening adverse event of some anticancer drugs. We compared treatment associated pneumonitis (TAP) related to immune checkpoint inhibitors (ICI) or chemotherapies (chemo) in advanced non-small cell lung cancer (aNSCLC) patients (pts) with and without (+/-) past medical history (PMH) of Pn, using data from clinical trials (CT) and real world data (RWD). Methods: Pts with PMH Pn in 8 aNSCLC CT comparing ICI to chemo, were identified using terms pneumonitis, acute interstitial pneumonitis, pneumonitis chemical, and interstitial lung disease. aNSCLC pts treated with ICI (+/- chemo) or chemo [without concurrent radiation therapy (RT)] were identified using RWD from a community health system; Pn was defined using terms in ICD-9 and ICD-10 including pneumonitis or associated concepts in the Unified Medical Language System. RWD pts were selected using core eligibility criteria from CT. In CT and RWD, Pn incidence proportion was calculated for 4 subgroups: pts (+/-) PMH of Pn and treated with ICI vs chemo. Pn diagnosis type, including RT Pn, was assessed. Results: In CT and RWD, a higher incidence of TAP was observed among aNSCLC pts with PMH of Pn compared to those without PMH of Pn, among ICI and chemo groups (Table 1). In CT pts without PMH of Pn, ICI associated Pn was more common than chemo associated Pn. Similar rates of TAP were observed in the CT and RWD. In RWD, Pn at any time was strongly associated with RT in ICI and chemo groups, with 73% of all diagnoses of Pn due to RT. Conclusion: PMH of Pn in pts with aNSCLC is associated with a greater risk of TAP for ICI and chemo groups, in CT and RWD. RWD data suggests RT to be a frequent cause of Pn. Only in CT data, and only for pts without PMH Pn, was there a demonstrated difference in TAP incidence between ICI and chemo groups. Additional research (e.g. inclusion of pts treated with tyrosine kinase inhibitors) is warranted to optimize treatment for cancer pts with PMH of Pn. Pneumonitis incidence and 95% CI among aNSCLC patients treated with immunotherapy and chemotherapyCT patients treated with immune checkpoint inhibitors +/-chemo (N=3723)CT patients treated with chemotherapies (N=2768)RWD patients treated with immune checkpoint inhibitors +/-chemo (N=615)RWD patients treated with chemotherapies (N= 647)patients with past medical history of pneumonitis (N=48 for CT; N=33 for RWD)5/30 (16.7%;7.3-33.6%)2/18 (11.1%;3.1-32.8%)3/21 (14.3%;5.0-34.6%)1/12 (8.3%; 0.4-35.4%)patients without past medical history of pneumonitis (N=6443 for CT; N=1229 for RWD)164/3693(4.4%; 3.8-5.2%)27/2750(1.0%; 0.7-1.4%)17/594 (2.9%; 1.8-4.5%)14/635 (2.2%; 1.3-3.7%)All patients (N=6491 for CTs; N=1262 for RWD)169/3723(4.5%; 3.9-5.3%)29/2768(1.0%; 0.7-1.5%)20/615 (3.3; 2.1-5.0%)15/647(2.3; 1.4-3.8%) Citation Format: Qi Liu, Chenan Zhang, Yutao Gong, Hao Zhu, Elaine Chang, Cheryl Cho-Phan, Jonathan Hirsch, Michael A. Thompson, Gideon Blumenthal, Shiew Mei Huang, Thomas D. Brown. Pneumonitis incidence in patients with non-small cell lung cancer treated with immunotherapy or chemotherapy in clinical trials and real-world data [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr CT086.

9606 Background: Higher PD-L1 score ≥ 50% predicts for greater benefit to immune checkpoint inhibitor (ICI) therapy in first line (1L) treatment of aNSCLC. It has recently been reported that PD-L1 score ≥ 90% predicts for even greater benefit to 1L ICI monotherapy (Aguilar et al., 2019). We examined pooled clinical trial databases to examine the relationship between high PD-L1 expression across multiple ICI monotherapies in 1L and second line (2L) treatment of aNSCLC. Methods: Data was pooled from trials (five 1L and five 2L) of ICI for the treatment of patients with aNSCLC. We defined PD-L1 score as the proportion of tumor cell stained by the assay (total of four assays identified) and included patients in the analysis with PD-L1 score ≥ 50%. Tumor-infiltrating immune cell staining was not considered. Progression-free survival (PFS) and overall survival (OS) by line of therapy for patients with PD-L1 score ≥ 90% and patients with PD-L1 score 50-89% was analyzed. Results: A total of 1320 patients treated with ICI monotherapy were identified, 873 in 1L and 447 in 2L. Median follow-up was 9.6 months in 2L patients and 13.3 months in 1L patients. Patients receiving 2L ICI therapy with PD-L1 score ≥ 90% (N = 208) had longer PFS and OS compared to patients with PD-L1 score 50-89% (N = 239), with mPFS 7.1 vs. 4.2 months (HR = 0.66 [95% CI: 0.52-0.83]) and mOS NR vs. 15.8 months (HR = 0.66 [95% CI: 0.49-0.89]). 1L ICI therapy analysis revealed similar trends, as patients with PD-L1 score ≥ 90% (N = 405) had longer PFS and OS compared to patients with a PD-L1 score 50-89% (N = 468), with mPFS 8.3 vs. 5.4 months (HR = 0.78 [95% CI: 0.66-0.92]) and mOS 22.9 vs. 16.4 months (HR = 0.74 [95% CI: 0.61-0.90]). Conclusions: This analysis showed the potential of an enhanced clinical benefit in patients with aNSCLC and PD-L1 score ≥90% across ICI monotherapies in both the 1L and 2L treatment setting. These data will be further analyzed in real world populations.

e15156 Background: Clinical trials show improved survival for advanced non-small cell lung cancer (aNSCLC) patients whose tumors are positive for PD-L1 expression when treated with immune checkpoint inhibitors (ICI), including pembrolizumab (Pb) and nivolumab (Nb). It is unclear whether relatively higher PD-L1 expression by tumor proportion score (TPS) is associated with better response to treatment, and whether this can be generalized to a real-world setting. Methods: We assessed overall survival (OS) across categories of PD-L1 expression levels among aNSCLC patients who received ICI monotherapy in the advanced/metastatic setting (stages IIIB or IV, or documented metastatic disease at diagnosis). Sub-analyses were performed based on first, second, or subsequent lines of treatment, as well as for patients receiving only Pb. The patient population is a sample from community health systems based in the United States, with data derived from electronic medical records and supplemented with molecular data integration from diagnostics labs. Results: 874 aNSCLC patients received ICI in the advanced/metastatic setting in the first line (n = 246, 28%), second line (n = 456, 52%), or third or later lines (n = 172, 20%). ICI-treated patients in any line with TPS of 1-49% (n = 148), 50-89% (n = 124), and 90-100% (n = 97) had OS of 6.9, 11.5, and 11.7 months, respectively. Pb-treated patients in any line with TPS of 1-49% (n = 38), 50-89% (n = 104), and 90-100% (n = 72) had OS of 5.5, 10.1, and 11.7 months, respectively. ICI-treated patients in the 1st line with TPS of 1-49% (n = 10), 50-89% (n = 80), and 90-100% (n = 59) had OS of 3.7, 8.0, and 7.4 months, respectively. Pb-treated patients in the first line with TPS of 1-49% (n = 7), 50-89% (n = 80), and 90-100% (n = 58) had OS of 3.7, 8.0, and 9.5 months, respectively. Conclusions: Results suggest OS benefit for real-world ICI-treated aNSCLC patients with PD-L1 TPS ≥50%, consistent with observations in clinical trials. The data further suggest additional benefits in the highest TPS category of 90-100% among Pb-treated patients, while the evidence is weaker for all ICI-treated patients, although comparisons did not reach statistical significance. A similar trend was seen in analyses of both patients treated in first-line only and in any line. Further analyses, to include comparison to clinical trial results, are warranted.

e15082 Background: Immune checkpoint inhibitor (ICI) therapy has become a mainstay of lung cancer treatment. However, not all NSCLC patients (pts) benefit, a subset paradoxically experience accelerated tumor growth while on immunotherapy. Hyperprogression (HP) refers to accelerated tumor growth on ICI with worsening clinical status. Various molecular alterations may be associated with HP including MDM2/MDM4 amplifications, EGFR aberrations, and STK11/LKB1 mutations. Kato et al. ( http://ow.ly/2n8a30nQpZv ) showed HP in 6/6 pts with MDM2/MDM4 amplification and in 2/10 pts with EGFR alterations. Methods: Lung cancer pts treated with ICI from Jan 2017 to Jan 2019 at Aurora Health Care were reviewed after IRB approved. Pts with NSCLC histology (ICD diagnosis codes and / or manual chart review), ICI treatment, and molecular testing were identified via the real world data (RWD) integrated in the Syapse platform. Additional chart review to ascertain HP was performed, and molecular results obtained via Syapse molecular lab integrations were analyzed. Pts had various forms of real world biomarker testing including oligo NGS panels. HP is defined as: 1) time-to-treatment failure (TTF) < 2 months (time from the start of treatment with ICI to ICI discontinuation for any reason, including progression, patient preference, toxicity, or death), 2) > 50% increase in tumor burden by RECIST, 3) spread of the disease to a new organ between baseline and first radiologic evaluation or clinical deterioration, and 4) ECOG PS ≥2 during the first 2 months of treatment. HP > = 3, Progression 1-2, non-progressor 0 criteria fulfilled.Pts with and without HP were compared using Chi-squared and Fisher Exact tests. T-tests were performed for continuous variables. Results: Out of 1536 lung cancer patients 350 (22.8%) were treated with ICI including: atezolizumab (35), durvalumab (6), nivolumab (177), pembrolizumab (145). Some pts were treated with more than one ICI. 64/350 (18.2%) pts had HP. 79/350 (22.5%) pts had progressive disease without meeting the definition of HP. Biomarker associations with HP are shown in the table. Conclusions: Only the STK11/LKB1 mutation was associated with HP (P = < 0.0001) with 5 of 6 STK11 pts treated with ICI showing HP. Other potential HP biomarkers will be assessed prospectively as larger panels are utilized. [Table: see text]

A group of disparate translational bioinformatics experts convened at the 6th Annual Precision Medicine Partnership Meeting, October 29–30, 2014 to discuss big data challenges and key strategic decisions needed to advance precision medicine, emerging solutions, and the anticipated path to success. This article reports the panel discussion.

Background: The ability to produce timely, clinically actionable recommendations is a cornerstone of a robust precision oncology program. This requires the assimilation of rapidly changing precision oncology data that flows asynchronously from various EMR and lab sources. A key challenge is harmonization of omics biomarkers from hospital-based and commercial testing labs, rendering these omics data interpretable and comparable between patients, labs and reports. To address this challenge, we describe an automated system leveraging a hybrid ontology and graph structure to permit the rapid harmonization and interpretation of molecular diagnostic results across multiple labs. Methods: A two-part, fully automated system to ingest and harmonize omics biomarker data from hospital-based and commercial testing labs was developed. First, an ontology-based omics lexicon provides annotation of discrete laboratory values provided electronically. The ontology model is Manchester language-based with data stored in a relational document store. Second, a graph structure serves as the knowledge model and relates the annotated lab values to 12 types of clinically informative biomarkers, including sequence and copy number variants, tumor mutational burden, MSI, gene rearrangements, wild type, and expression biomarkers. The graph structure leverages the ontology to fully describe hierarchical and categorical data associated with each biomarker. Access to the omics knowledge model uses a RESTful API and relational database architecture. Acquisition of molecular data uses custom JSON schemas and a RESTful API. Results: Feeds from 7 commercial and hospital-based labs resulted in the receipt of >12,000 molecular diagnostic reports containing >2 million individual biomarker observations, with integration of each report achieved within 2 minutes of electronic data receipt. As of Nov. 2018, 81.2% of reports had at least one biomarker observation, while the remaining reports lacked results. Within these biomarker observations, 95.8% were represented in the ontology/graph structure, resulting in successful linkage to ~22,000 distinct harmonized biomarkers out of more than 12 million in the knowledge base. Of the linked, harmonized variant biomarkers, 4% are class-level (e.g. BRAF mutation) with the remainder reflecting more specificity (e.g. BRAF V600E). Within the set of more specific biomarkers, 54% represent a protein altering variant biomarker. Conclusions: We have built an automated, scalable system using a novel ontology/graph structure to reliably and automatically harmonize and integrate omics data into a real-world oncology precision medicine platform. Proof of concept validation has been demonstrated in over 12,000 patient reports, with the results being used to enable clinical trials matching and outcomes research. Citation Format: James E. Shima, James L. Chen, Matthew J. Glick, Ryan A. Warrier, Eric C. Abruzzese, Walter C. Mankowski, Jonathan Hirsch. A hybrid ontology and graph system enabling precision oncology applications through real-time incorporation of omics biomarkers into a scalable real-world data platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1676.

e18070 Background: Real world data (RWD) is increasingly being used to generate evidence that informs clinical care. Calculating outcomes measures using RWD, such as time-on-treatment (ToT), requires accurate medication start/end dates. Whereas intravenously administered medication dates are typically available, dates for oral antineoplastics (OANs) are challenging as they are filled by specialty pharmacies and documented separately. To determine the feasibility of automated ToT extraction, we used the Syapse Learning Health Network to compare the utility of automated chart extraction (ACE) and of manual chart abstraction (MCA) from the electronic health record (EHR) in providing high-quality OAN data. Methods: We selected cancer patients (pts) from two histologies for whom OANs were prescribed. For these pts, ACE was compared to MCA. ACE data were derived from EHR structured medication lists through existing interoperability pipelines. MCA was performed by 4 trained data abstractors who reviewed the corresponding progress notes per pt. Expected date of OAN start/end, and actual medication start/end, were recorded as available. Chi-square and descriptive statistics were used for analysis. Results: 61 cancer pts (31 lung, 30 breast; mean age 62y [27-90]; 20% male) who received OAN from 3 multi-hospital medical systems were evaluated. ACE detected a greater number of expected start/end dates as compared to MCA (Table, P < 0.001). In contrast, for actual start/end dates, the converse was true; ACE was inferior to MCA (P < 0.001). Noteworthy, only 26% of pts had actual start/end dates using manual chart abstraction only. There was no concordance between the actual ACE and MCA dates. We evaluated if ACE expected ToT dates could be used as a surrogate for actual MCA ToT dates. Of the 12 pts satisfying this criteria, mean discordance in ToT was 19 days (1-71 days). Conclusions: MCA only captured actual ToT in a small minority of pts. ACE expected dates were a poor surrogate for ToT and highly discordant to over 2 months. Neither MCA nor ACE from EHR data were adequate for the majority of pts. Alternative mechanisms such as integration with additional data sources like specialty pharmacy dispensing records are essential. [Table: see text]

e18099 Background: Real World Data (RWD) is being used for outcomes research and regulatory submissions. A key variable needed to understand treatment outcomes is Line of Therapy (LoT). However, LoT is generally not captured in RWD sources such as electronic health records (EHR) or claims data, and is typically derived using manual abstraction. To determine whether an automated approach to LoT derivation is possible, we created an algorithm and applied it to patients (pts) in the Syapse Learning Health Network. Methods: We selected confirmed NSCLC pts from 4 health systems in the RWD set, verifying diagnosis using ICD-9/10/O3 topography and morphology codes. We analyzed the EHR-derived medication list using a regimen-independent algorithm that classified antineoplastic drugs (AD), as defined by ATC L01, into LoT. Within each LoT, we compared the top 80% of AD prescribed (by volume of pts) to the LoT as indicated on each drug’s FDA label. We then used descriptive statistical summaries to outline the alignment between automated algorithmic results and indicated usage within that LoT. Results: In a set of 10,842 NSCLC pts, a total of 106 unique AD were prescribed in the first line as identified by our algorithm, and 13 drugs were prescribed as first line for 80% of the pts. Of those, 9 (69%) of those are indicated for first line, 3 are not indicated for NSCLC, and 1 is indicated for a subsequent NSCLC line, per FDA labels. 82 unique AD were prescribed in the second line as identified by our algorithm, and 15 drugs were prescribed as second line for 80% of the pts. Of those, 11 (73%) are indicated for treatment/continuation therapy for recurrent, advanced or metastatic disease, 3 are not indicated for NSCLC, and 1 is indicated for first line NSCLC per FDA labels. 36 unique AD were prescribed in subsequent line as identified by our algorithm, and 18 drugs were prescribed as subsequent line for 80% of the pts. Of those, 12 (67%) are indicated for treatment of recurrent, advanced or metastatic disease or subsequent systemic therapy, 5 are not indicated for NSCLC and 1 is indicated for first line per FDA labels. Conclusions: An automated algorithmic approach for deriving lines of therapy may be a viable solution to scalably calculate LoT in RWD sets. A deeper analysis using statistical sensitivity and specificity assessment of such algorithms is needed to validate the potential of an algorithmic approach.

e18515Background: Many health systems seek the ability to share and learn from real-world evidence, or aggregated cancer patient data, to improve patient outcomes. Although precision medicine initi...

e18763Background: The lack of interoperability among different electronic medical record (EMR) systems remains a challenge to fulfilling the promises of precision oncology. Typically, cancer outcom...

6539Background: Precision medicine (PM) molecular panel (MP) testing report actionable findings with associated targeted therapies (including immunotherapies). However, these actionable findings “r...

Purpose. AlbugraninTM fusion protein is recombinant granulocyte colony stimulating factor (rG-CSF) genetically fused at its N-terminus to the C-terminus of recombinant serum human albumin and is expected to have a relatively long half-life compared with rG-CSF alone. In this study, the pharmacodynamics and pharmacokinetics of Albugranin were evaluated in BDF1 mice and cynomolgus monkeys.

Recently an association between statins and the onset and more rapid disease course of amyotrophic lateral sclerosis (ALS) was reported, while other studies rejected such a link. The role of gender in that controversy is unclear. We evaluated the gender-specific effect of statins on the rate of functional decline in patients with ALS, based on data retrieved from the medical records of all ALS patients who participated in two previously reported clinical trials on the efficacy of topiramate and of celecoxib in ALS. The topiramate trial enrolled 294 patients, 28 (9.5%) of whom were statin users (20 males). The celecoxib trial enrolled 300 patients, 25 (8.3%) of whom were statin users (17 males). Statins had no effect on the functional decline in the celecoxib trial, but they did have a negative impact on disease course in the topiramate trial. When males and females were analyzed separately, the functional decline of females taking statins was significantly greater than that of males in both trials. Our results indicate that statins affect possibly negatively ALS progression among females but not males. They emphasize the need to consider gender in future analyses of drug effects.

e17521 Background: Precision medicine has the potential to revolutionize cancer care by matching the right patient to the right therapy. Using genomics in routine care to guide therapy selection re...

Albugranin fusion protein is recombinant granulocyte colony stimulating factor (rG-CSF) genetically fused at its N-terminus to the C-terminus of recombinant serum human albumin and is expected to have a relatively long half-life compared with rG-CSF alone. In this study, the pharmacodynamics and pharmacokinetics of Albugranin were evaluated in BDF1 mice and cynomolgus monkeys.Single doses of Albugranin (0.25-5 mg/kg) or Filgrastim (methionyl rG-CSF, 0.25, or 1.25 mg/kg) were administered subcutaneously (SC) to mice and multiple doses of Albugranin (25-100 microg/kg every 4 or 7 days) or Filgrastim (5 microg/kg daily) were administered SC for 14 days to monkeys for hematologic evaluation. For pharmacokinetics studies, mice were injected intravenously (IV) or SC with single doses of Albugranin (0.25-1.25 mg/kg) or Filgrastim (0.25 mg/ kg) and monkeys were injected SC with multiple doses of Albugranin (100-1,000 microg/kg once weekly for 5 weeks). Plasma levels of Albugranin and Filgrastim were measured by enzyme-linked immunosorbent assay.In mice, administration of Albugranin effectively increased the number of peripheral granulocytes and mobilized hematopoietic progenitor cells for up to 5 days. The magnitude and duration of this effect were dose-dependent. In contrast, administration of Filgrastim resulted in a small increase in both cell types on day 1 only. Albugranin administered to cynomolgus monkeys caused an increase in peripheral neutrophils, with a less prominent increase in peripheral monocytes. Albugranin-induced neutrophilia peaked 24 h following each dose administration. Administration of Filgrastim daily in monkeys resulted in moderate increases in neutrophils that were maximal on days 8-12 during the course of treatment. Compared with Filgrastim, Albugranin had a longer terminal half-life (t(1/2,term)) and mean residence time (MRT), and slower clearance (CL/F) in mice. The t(1/2,term), MRT, and CL/F of Albugranin following SC administration to BDF1 mice were 5.6-5.7 h, 16.7-20.7 h, and 6.37-12.2 mL/h/kg, respectively, compared with 2.54 h, 4.9 h, and 164 mL/h/kg, respectively for Filgrastim. In cynomolgus monkeys, the corresponding values of t(1/2,term), MRT, and CL/F for Albugranin were 7.73-133 h, 19.4-27.3 h, and 7.90-27.5 mL/h/kg, respectively, for doses of 100-1000 microg/kg. An exposure-response relationship that could be empirically described with a simple Emax model with baseline was found between day 15 absolute neutrophil count and area under the curve following the first dose in cynomolgus monkeys.The sustained activity of Albugranin in mice and monkeys demonstrated in these studies suggests that this agent could be given less frequently than Filgrastim to achieve similar therapeutic effects in patients.

ObjectiveThe best approach for Helicobacter pylori management remains unclear. An audit process is essential to ensure clinical practice is aligned with best standards of care.DesignInternational multicentre prospective non-interventional registry starting in 2013 aimed to evaluate the decisions and outcomes in H. pylori management by European gastroenterologists. Patients were registered in an e-CRF by AEG-REDCap. Variables included demographics, previous eradication attempts, prescribed treatment, adverse events and outcomes. Data monitoring was performed to ensure data quality. Time-trend and geographical analyses were performed.Results30 394 patients from 27 European countries were evaluated and 21 533 (78%) first-line empirical H. pylori treatments were included for analysis. Pretreatment resistance rates were 23% to clarithromycin, 32% to metronidazole and 13% to both. Triple therapy with amoxicillin and clarithromycin was most commonly prescribed (39%), achieving 81.5% modified intention-to-treat eradication rate. Over 90% eradication was obtained only with 10-day bismuth quadruple or 14-day concomitant treatments. Longer treatment duration, higher acid inhibition and compliance were associated with higher eradication rates. Time-trend analysis showed a region-dependent shift in prescriptions including abandoning triple therapies, using higher acid-inhibition and longer treatments, which was associated with an overall effectiveness increase (84%–90%).ConclusionManagement of H. pylori infection by European gastroenterologists is heterogeneous, suboptimal and discrepant with current recommendations. Only quadruple therapies lasting at least 10 days are able to achieve over 90% eradication rates. European recommendations are being slowly and heterogeneously incorporated into routine clinical practice, which was associated with a corresponding increase in effectiveness.