Tocilizumab in patients hospitalised with COVID-19 pneumonia: Efficacy, safety, viral clearance, and antibody response from a randomised controlled trial (COVACTA)

BACKGROUND

In COVACTA, a randomised, placebo-controlled trial in patients hospitalised with coronavirus disease-19 (COVID-19), tocilizumab did not improve 28-day mortality, but shortened hospital and intensive care unit stay. Longer-term effects of tocilizumab in patients with COVID-19 are unknown. Therefore, the efficacy and safety of tocilizumab in COVID-19 beyond day 28 and its impact on Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) clearance and antibody response in COVACTA were investigated.

METHODS

Adults in Europe and North America hospitalised with COVID-19 (N = 452) between April 3, 2020 and May 28, 2020 were randomly assigned (2:1) to double-blind intravenous tocilizumab or placebo and assessed for efficacy and safety through day 60. Assessments included mortality, time to hospital discharge, SARS-CoV-2 viral load in nasopharyngeal swab and serum samples, and neutralising anti-SARS-CoV-2 antibodies in serum. ClinicalTrials.gov registration: NCT04320615.

FINDINGS

By day 60, 24·5% (72/294) of patients in the tocilizumab arm and 25·0% (36/144) in the placebo arm died (weighted difference -0·5% [95% CI -9·1 to 8·0]), and 67·0% (197/294) in the tocilizumab arm and 63·9% (92/144) in the placebo arm were discharged from the hospital. Serious infections occurred in 24·1% (71/295) of patients in the tocilizumab arm and 29·4% (42/143) in the placebo arm. Median time to negative reverse transcriptase-quantitative polymerase chain reaction result in nasopharyngeal/oropharyngeal samples was 15·0 days (95% CI 14·0 to 21·0) in the tocilizumab arm and 21·0 days (95% CI 14·0 to 28·0) in the placebo arm. All tested patients had positive test results for neutralising anti-SARS-CoV-2 antibodies at day 60.

INTERPRETATION

There was no mortality benefit with tocilizumab through day 60. Tocilizumab did not impair viral clearance or host immune response, and no new safety signals were observed. Future investigations may explore potential biomarkers to optimize patient selection for tocilizumab treatment and combination therapy with other treatments.

FUNDING

F. Hoffmann-La Roche Ltd and the US Department of Health and Human Services, Office of the Assistant Secretary for Preparedness and Response, Biomedical Advanced Research and Development Authority, under OT number HHSO100201800036C.

Prognostic and Predictive Biomarkers in Patients With Coronavirus Disease 2019 Treated With Tocilizumab in a Randomized Controlled Trial

OBJECTIVES

To explore candidate prognostic and predictive biomarkers identified in retrospective observational studies (interleukin-6, C-reactive protein, lactate dehydrogenase, ferritin, lymphocytes, monocytes, neutrophils, d-dimer, and platelets) in patients with coronavirus disease 2019 pneumonia after treatment with tocilizumab, an anti-interleukin-6 receptor antibody, using data from the COVACTA trial in patients hospitalized with severe coronavirus disease 2019 pneumonia.

DESIGN

Exploratory analysis from a multicenter, randomized, double-blind, placebo-controlled, phase 3 trial.

SETTING

Hospitals in North America and Europe.

PATIENTS

Adults hospitalized with severe coronavirus disease 2019 pneumonia receiving standard care.

INTERVENTION

Randomly assigned 2:1 to IV tocilizumab 8 mg/kg or placebo.

MEASUREMENTS AND MAIN RESULTS

Candidate biomarkers were measured in 295 patients in the tocilizumab arm and 142 patients in the placebo arm. Efficacy outcomes assessed were clinical status on a seven-category ordinal scale (1, discharge; 7, death), mortality, time to hospital discharge, and mechanical ventilation (if not receiving it at randomization) through day 28. Prognostic and predictive biomarkers were evaluated continuously with proportional odds, binomial or Fine-Gray models, and additional sensitivity analyses. Modeling in the placebo arm showed all candidate biomarkers except lactate dehydrogenase and d-dimer were strongly prognostic for day 28 clinical outcomes of mortality, mechanical ventilation, clinical status, and time to hospital discharge. Modeling in the tocilizumab arm showed a predictive value of ferritin for day 28 clinical outcomes of mortality (predictive interaction, p = 0.03), mechanical ventilation (predictive interaction, p = 0.01), and clinical status (predictive interaction, p = 0.02) compared with placebo.

CONCLUSIONS

Multiple biomarkers prognostic for clinical outcomes were confirmed in COVACTA. Ferritin was identified as a predictive biomarker for the effects of tocilizumab in the COVACTA patient population; high ferritin levels were associated with better clinical outcomes for tocilizumab compared with placebo at day 28.

Therapeutic Monitoring of Circulating DNA Mutations in Metastatic Cancer with Personalized Digital PCR

As a high-performance solution for longitudinal monitoring of patients being treated for metastatic cancer, a single-color digital PCR (dPCR) assay that detects and quantifies specific cancer mutations present in circulating tumor DNA (ctDNA) was developed. This customizable assay has a high sensitivity of detection. One can detect a mutation allelic fraction of 0.1%, equivalent to three mutation-bearing DNA molecules among 3000 genome equivalents. The objective of this study was to validate the use of personalized dPCR mutation assays to monitor patients with metastatic cancer. The dPCR results were compared with serum biomarkers indicating disease progression or response. Patients had metastatic colorectal, biliary, breast, lung, and melanoma cancers. Mutations occurred in essential cancer drivers such as BRAF, KRAS, and PIK3CA. Patients were monitored over multiple cycles of treatment for up to a year. All patients had detectable ctDNA mutations. The results correlated with serum markers of metastatic cancer burden, including carcinoembryonic antigen, CA-19-9, and CA-15-3, and qualitatively corresponding to imaging studies. Corresponding trends were observed among these patients receiving active treatment with chemotherapy or targeted agents. For example, in one patient under active treatment, increasing quantities of ctDNA molecules were detected over time, indicating recurrence of tumor. This study demonstrates that personalized dPCR enables longitudinal monitoring of patients with metastatic cancer and may be a useful indicator for treatment response.

Abstract 2278: A high throughput method for the optimization of digital PCR assays for personalized circulating tumor DNA detection

Single color digital PCR (sc-dPCR) is a robust approach for the quantitation of low allelic fraction mutations in clinical oncology samples. More recently this technology has been employed to identify mutations from circulating tumor DNA (ctDNA) that has been extracted from the blood samples of cancer patients. The use of digital PCR has great potential for non-invasive longitudinal monitoring via liquid biopsies. However, this application requires low input DNA volumes and relies on a single nucleotide variant (SNV) to distinguish between normal and ctDNA, necessitating that sc-dPCR primer binding is both highly efficient and specific. These stringent requirements make assay optimization a tedious process that greatly limits the rate at which personalized detection panels can be generated. We have developed a high throughput method to optimize sc-dPCR assays utilizing Next Generation Sequencing (NGS) technology to assess amplification more quickly and with more flexibility than traditional gel based analysis.

Using our assay optimization approach, a segment of each gene containing a tumor specific SNV was incorporated into the genome of Saccharomyces cerevisiae. These renewable positive control colonies were cultured in a 96 well plate format and pooled to mimic the low allelic frequency conditions of ctDNA. The presence of each tumor specific SNV was confirmed by preparing and sequencing a library containing the unique barcode region of each colony. Using bulk PCR, up to 96 primer sets were tested at one annealing temperature in a singleplex format. Alternatively, we multiplexed up to 11 primers in each well, greatly increasing the number of assays that can be developed per plate. Using this multiplexed format, we introduced a thermal gradient across the plate to identify the optimal annealing temperature of each primer set in a single run. A parallel experiment with identical PCR conditions was run using NA18507 human DNA to act as a negative control for primer specificity.

All amplicons in each PCR condition were uniquely indexed and sequenced using an NGS platform. Using a ratio of the number of reads associated with on target and non-mutation specific amplicon sequences for each primer set, the success of each assay was determined. This method was also used to identify specific mismatches incorporated in the primer sequence that increased binding specificity. Using a sequencing based analysis method, we have observed that sc-dPCR assays can be optimized rapidly across multiple mutations, making them more accessible for personalized monitoring.

Citation Format: Maya M. Arce, Christina Wood-Bouwens, Derrick Haslem, Billy T. Lau, John Bell, Alison Almeda, Matt Kubit, Bryce Moulton, Robin Romero, Robert P. St. Onge, Lincoln Nadauld, Hanlee P. Ji. A high throughput method for the optimization of digital PCR assays for personalized circulating tumor DNA detection [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 2278.

Abstract 998: OPeN: the oncology precision network data sharing consortium

Background: The advent of Next-Generation Sequencing (NGS), and other molecular diagnostic technologies, has enabled the use of genomic information to guide targeted treatment in cancer patients. While this precision oncology approach can yield exciting clinical outcomes, the innumerable genomic variants identified in individual tumors effectively establishes each case as a unique N=1 clinical presentation. This scenario is contrary to a basic dogma of medical practice where historical cases and treatment outcomes guide future management and therapeutic decisions. Aggregation of large data sets, on a multi-institutional basis, has the potential to overcome the N=1 paradox and yield management insights in the implementation of precision oncology.

Methods: We have formed the Oncology Precision Network (OPeN), an oncology data sharing consortium, to aggregate big data sets consisting of clinical, genomic, pharmacological, and treatment response data from diverse patient cases. Data from Intermountain Healthcare, Stanford University, and Swedish Cancer Institute-Providence St. Joseph Health, as well as other institutions, comprises the database and is derived from 79 hospitals, over 800 physician clinics and more than 50,000 annual cases.

Results: The OPeN database can be interrogated by variant type, specific therapeutics, clinical outcomes, and by grouped variables, in a structured data format. The overarching IT platform is a cloud based, open source, triple store precision oncology solution, Syapse. These data are yielding valuable insights, including tumor mutational burden (TMB) scores and their correlation to immunotherapy response, clinical response in various drug-gene combinations, and therapy-specific adverse events.

Conclusions: We anticipate this resource will be used by the Molecular Tumor Boards of contributing institutions for clinical interpretation, and by treating providers to overcome the N=1 challenge associated with precision oncology.

Citation Format: Lincoln Nadauld, Derrick Haslem, Paul D. Tittel, Mariko Tameishi, Thomas Brown, James Ford. OPeN: the oncology precision network data sharing consortium [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 998. doi:10.1158/1538-7445.AM2017-998

Abstract 3650: Multi-pronged approach to establish control standards for somatic mutations in next generation sequencing (NGS) oncology test

In recent years, somatic mutation testing via Next Generation Sequencing (NGS) has emerged as a powerful tool to detect targetable mutations in diseases such as cancer. These include mutations such as BRAF V600E, which can lead to targeted drug therapy; therefore, improving the standard of care in cancer diagnostics. To generate clinically meaningful results, we need to define standards that can be applied to laboratories performing somatic testing on tumor samples. With ongoing debate about the use of positive or negative controls in somatic testing assays, we designed an experiment to test the concordance of clinically actionable mutations commonly seen in tumor testing. We use cell line controls and commercially engineered DNA to validate concordance of mutations at specific allelic ratios. Our results depict an experiment design to determine if a genomic test can detect actionable mutations with high levels of accuracy and precision.

In this study, we designed a multi-pronged approach to evaluate the need for control standards by the ICG100 clinical NGS panel. To establish a baseline negative control, we performed concordance testing on the NA12878 cell line. We compared SNPs, insertions and deletions found using our methodology to the variants reports by NIST. We found our results to be concordant with NIST at a sensitivity of 92% and a specificity of 93%. To establish a baseline for positive controls, we utilized commercially engineered DNA which contains variants spiked-in at known allelic frequencies. This allowed us to determine if the ICG100 panel was able to retrieve specific somatic mutations. We were able to detect high confidence somatic mutations, such as BRAFV600E, as well as BRAF V600G which was spiked in at a lower expect allelic frequency of 4%. Moreover, we are able to detect with high confidence mutations such as ALK F1174L, EGFR G719S, PIK3CA H1047R, and MET Y1247D, and we were able to reproduce the results across multiple cell lines. Overall, our results show the need to utilize controls as standard protocol which can help assess the proficiency of a clinical assay. With rapid advances is NGS testing methodologies, there is a need for establishing standardized controls that asses the performance of a somatic tumor testing.

Citation Format: Christopher Johnson, Sharanya Raghunath, Jackie Wayne, Aimee Shamo, Patrick Bradley, Moises Hernandez, David Loughmiller, Jason Gillman, Derrick Haslem, Gary Stone, Lincoln Nadauld, Pravin J. Mishra. Multi-pronged approach to establish control standards for somatic mutations in next generation sequencing (NGS) oncology test. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3650.

Abstract PR07: Precision genomic medicine improves clinical outcomes in advanced cancer patients

Background: The advent of Next-Generation Sequencing (NGS), and other diagnostic technologies, has enabled the use of genomic information to guide targeted treatment in cancer patients. Utilizing these technologies, we established a precision medicine program within a large, integrated healthcare delivery system. We then monitored the outcomes, including progression free survival and treatment delivery costs, associated with the delivery of precision medicine for patients with advanced cancer. We report the structure of our program and an analysis of the clinical outcomes associated with precision cancer medicine.

Methods: We conducted a matched cohort study of 72 patients from July 01, 2013 to December 31, 2014, with metastatic cancer of diverse subtypes. The outcomes of 36 patients treated with precision cancer medicine were compared to 36 historical control patients who received standard chemotherapy. Study and control patients were matched according to age, gender, histological diagnosis, and number of previous treatment lines. Progression free survival was compared between the two groups using a Cox Proportional Hazard model for survival and accounting for potential confounders. Costs included subsequent ED visits, hospitalizations, NGS costs, and costs for targeted treatment or standard therapy.

Results: Establishing a precision cancer medicine program for advanced cancer patients was feasible and scalable. Evaluation of the outcomes revealed that progression free survival was 22.9 weeks for the treatment group and 12.0 weeks for the historical control group (p = 0.002). Patients receiving precision cancer medicine compared to conventional treatment patients had a hazard ratio of 0.47 (95% confidence interval of 0.29-0.75) when adjusting for age, gender, histological diagnosis and previous treatment lines. Cost per week was $3,204 in the treatment group and $3501 in the historical control group, p = 0.22

Conclusions: Precision cancer medicine appears to significantly improve survival for patients with advanced cancer when compared to control patients who received conventional chemotherapy. The additional survival is not associated with increased health care costs. While the results of this study warrant further investigation, this genomics-based approach appears to be a viable, and perhaps superior, option for patients with advanced or metastatic cancer.

This abstract is also presented as Poster 16.

Citation Format: Lincoln D. Nadauld, Burke Van Norman, Gail Fulde, David newman, Allison Butler, Brian Tudor, Heather Gilbert, Karen Lin, Gary Stone, Anish Konde, Iva Petrovchich, James M. Ford, Derrick Haslem. Precision genomic medicine improves clinical outcomes in advanced cancer patients. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Integrating Clinical Genomics and Cancer Therapy; Jun 13-16, 2015; Salt Lake City, UT. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(1_Suppl):Abstract nr PR07.

Abstract 1114: Genomics in cancer patient care: Bench to bedside and beyond

Burgeoning sequencing technologies and the slow pace to use genomics data clinically has been largely hampered by lack of unestablished clinical utilities. There is an immediate need to store, analyze and retrieve meaningful clinical information from high throughput genomics data. At Intermountain Cancer Genomics (ICG) we created a complete translational pipeline that integrates these major core aspects: a clinical laboratory that generates data targeted within our gene panel, a bioinformatics pipeline that accounts for the quality of the data and further generates a set of variants that can be interpreted and targeted clinically to improve the quality of a patient's life.

At the ICG clinical laboratory we have developed a comprehensive ICG100 targeted sequencing panel under CLIA-CAP guidelines. DNA extracted from patient's tumor specimen gets sequenced for the entire coding region of 96 cancer-related genes which are often altered in cancer. These targeted regions are sequenced on Illumina's MiSeq sequencing platform using an in-solution, oligo-capture sequencing method. This test offers high coverage (>100X) and detects all classes of genomic alterations, including indels, translocations, copy number alterations (CNAs), and point mutations across the exons of 96 genes. This approach is viable and well-suited for all sample types including FFPE, fresh tissue and plasma.

We have developed a comprehensive bio-analytics pipeline that accommodates the diverse variants generated by the unique sequencing chemistry. Comparison of ICG100 to a commercially available CLIA-certified sequencing test that also detects copy number alterations, reveals high concordance across the spectrum of variant types. In addition, the ICG100 test detected 10 additional CNAs across 6 separate samples that were not identified in the commercially available test, suggesting an increased sensitivity with ICG100.

This integrated service utilizes a collaborative molecular tumor board that consist of subject expert scientists and physicians. Interdisciplinary tumor board suggests effective treatment options based on genomics data and clinical relevance. ‘Actionable’ genomic alterations are categorized as such if linked to an approved therapy in the solid tumor examined or another solid tumor. This test can be ordered by oncologist through a simple web-based interface where genomic results and molecular tumor board interpretation can be viewed. Additionally, oncologists can make a treatment selection and order drug at their convenience.

The ICG100 test therefore not only is cost-effective but offers higher sensitivity, coverage, superior ability for clinical management with identification of actionable CNAs, genomics-driven personalized treatment and precision cancer care.

Citation Format: Sharanya Raghunath, David Loughmiller, Aimee Shamo, Jackie Wayne, Patrick Bradley, Jason Gillman, Gary Stone, Derrick Haslem, Lincoln Nadauld, Pravin J. Mishra. Genomics in cancer patient care: Bench to bedside and beyond. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1114. doi:10.1158/1538-7445.AM2015-1114

Success rate of direct percutaneous endoscopic jejunostomy in patients who are obese

BACKGROUND

Direct percutaneous endoscopic jejunostomy (DPEJ) is increasingly used as a method for obtaining jejunal enteral access. The most cited reason of unsuccessful placement is poor transillumination, which may be related to obesity. Whether obesity affects failure and complication rates has not been previously described.

OBJECTIVE

To compare the success rate and adverse events (AEs) associated with DPEJ placement in patients who were overweight and patients who were obese compared with patients who were normal or underweight defined by body mass index (BMI).

DESIGN

Retrospective database review.

SETTING

A tertiary-referral center.

PATIENTS

Eighty DPEJ placements between February 2000 and September 2005.

MAIN OUTCOME MEASUREMENTS

DPEJ placement success in patients who were overweight/obese (BMI >or= 25) versus patients who were normal or underweight (BMI <25). Secondary end points included procedure time and AEs.

RESULTS

Eighty DPEJs were placed in 75 patients. Of these DPEJs, 65 (81%) succeeded and 15 (19%) failed. Success rates were 23 of 24 for patients who were underweight (96%), 25 of 31 for patients with normal BMI (81%), 8 of 11 for patients who were overweight (73%), and 6 of 10 for persons who were obese (60%) (odds ratio 3.43, 95% CI 1.03-11.44; P< .05 for BMI >or= 25 vs BMI<25). Overall, AEs were not significantly different for patients with BMI <25 versus BMI >or=25 (24/55 vs 9/21, respectively; P= .64). However, 4 of the 5 severe AEs occurred in patients with a BMI >or= 25 (P= .07).

LIMITATIONS

Retrospective single center.

CONCLUSIONS

DPEJ placement in patients who were overweight or obese was feasible, but procedural success was less frequent, and a trend toward more frequent major AEs was seen than in persons with normal or decreased BMI. BMI was an easily assessed preprocedural factor for DPEJ success and complication rates.