One Company’s Trash: Nephrology’s Collaboration With Industry in the Fight Against COVID-19

It all started with leftovers. Ascend Clinical laboratories was already taking regular (typically monthly) blood samples of its thousands of dialysis patients from centers all around the country when the pandemic hit. And they, like so many others, wanted to help at a time when so many felt helpless.

They were already planning to obtain the capability to test for COVID-19 antibodies but realized they could also potentially test some of the remnant blood they had on hand that they usually throw away. So they reached out to Glenn Chertow, MD, then division chief of nephrology and current Norman S. Coplon Satellite Healthcare professor of nephrology, wondering whether they might be able to help in the fight against COVID-19.

The Idea

The thought was first broached during a coffee break. Chertow and Ascend CEO Paul Beyer, who’ve known each other for several years, met on a windy afternoon in early spring, when COVID-19 was first starting to surge in New York. “We were basically lamenting how powerless we were and what we could possibly do to contribute to the fight against this virus,” Chertow remembers. Their thoughts first turned to testing, and then to antibody testing, and soon the project was born.

“This is basically a story of two frustrated people, one business person and one doctor, sort of knocking heads together over a cup of coffee,”Chertow explains. Beyer told Chertow about the samples he had access to.

“It clicked in my head, well, this would be an unbiased sample,” Chertow says, “because it’s a population of patients who get their blood drawn on a routine basis because of the nature of their treatment.” If they tested these patients for COVID-19 antibodies, they’d be able to get a fairly clear picture of what the COVID-19 prevalence was in the U.S.

“This is basically a story of two frustrated people, one businessperson and one doctor, sort of knocking heads together over a cup of coffee”

“It clicked in my head, well, this would be an unbiased sample,” Chertow says, “because it’s a population of patients who get their blood drawn on a routine basis because of the nature of their treatment.” If they tested these patients for COVID-19 antibodies, they’d be able to get a fairly clear picture of what the COVID-19 prevalence was in the U.S.

The idea was promising, but one crucial hurdle remained: how to pay for it. Most dialysis patients are covered by Medicare, which couldn’t cover the costs for a study that didn’t lead to direct patient action. So Beyer volunteered to cover them. “It was an incredibly generous gesture on his part,” Chertow states. He accepted the offer, and they moved forward.

The next step was assembling the team.

The Team

The team was composed of Chertow; Shuchi Anand, MD, assistant professor of nephrology; biostatisticians Maria Montez-Rath, PhD, senior research engineer of nephrology, and Jialin Han, MS; and epidemiologist Julie Parsonnet, MD, George DeForest Barnett professor of medicine. They decided to study the remnant blood for the presence of COVID-19 antibodies (also known as “seroprevalence”) and then analyze the anonymized data based on geographical region, ethnicity, and other data points. The process started in June 2020, testing was done throughout the month of July, and initial data were submitted in mid-August, a blisteringly fast pace for this kind of research.

Maria Montez-Rath, PhD

The Team

Nearly all of them worked from home. One of the greatest challenges, Anand explains, came from an overall positive: They had almost too much data coming at them too fast. “We just really had to work hard to interpret it and present it in a rigorous manner,” she says. “And our team was really holding itself to a high standard to do that well.”

As the principal biostatistician of the group, Montez-Rath both planned and designed the data analysis, working “many hours” on the “very intense” project. She adds, “In a pandemic, all data becomes outdated very quickly and new knowledge is created at a very fast pace, which makes it even harder to maintain high-quality work. Given that all my other projects didn’t stop when the pandemic started, it resulted in many more hours of work (including nights and weekends) beyond what I would normally do.”

Still, she remembers the work fondly. “I immediately realized that the project was going to have a really high impact,” she says. Her enthusiasm for her work kept her going. As she explains, “I have my dream job: working closely with people in various projects that ideally have an impact on people. I feel that what I do is useful to patients and to the betterment of the world.”

Han, a biostatistician hired at Stanford in 2018, echoes Montez-Rath’s passion for meaningful work: “It’s always interested me that my work could improve people’s quality of life,” he says. He heard about the project in June 2020, when Montez-Rath realized there was too much statistical work to do all by herself. He describes the hectic pace of the process this way: “We met frequently to summarize the research questions and the analysis plan. It all came really fast, especially since at that time there was no report about national seroprevalence at all. The idea was if we want to do this, we have to do it fast.”

And he means fast—some days he met the team at 7 a.m. to discuss a problem and then again at 5 p.m. that same day to track the progress. He describes the work as “really intense and time sensitive,” but adds, “We understood the importance of this study, so we wanted to do the best we could.” His role included data preparation, data mining, data analysis, and output generation.

Parsonnet was brought on board for her epidemiological expertise, giving opinions on study design and meeting regularly with the team to “discuss what the data showed and go over it and review what it meant and how we interpreted it, given the world around us.” It was her first collaboration with this team and she found it to be “just such a pleasure.”

Shuchi Anand, MD

The Study

Initially, Anand recalls, “it was important to understand in real time what was happening with the epidemic.” Ascend’s data drew from 46 states and a third of all counties in the U.S., spread from coast to coast.

Forty percent of the samples were from patients 65 and older, and since patients on dialysis are often from disproportionately disadvantaged populations, racial and ethnic minorities and people from poorer neighborhoods were actually overrepresented in the population of the study. “That was great,” Anand explains, “because those groups are often the most vulnerable to SARS-CoV-2 but are so hard to reach via a door-to-door survey.”

The researchers were also able to use the results from this population to extrapolate. “Our main goal was not just to provide a sample that was representative of the Ascend dialysis population but also to then analyze the data so it could represent both the overall dialysis population and the general adult population of the U.S.,” Montez-Rath states.

The Results

The results came quickly: Regional and ethnic differences made a significant impact on the prevalence of COVID-19 antibodies (and, therefore, the rates of COVID-19 infection in various communities). The intense outbreak at the time was in New York City, and seroprevalence was up to approximately 25% in New York City at the time of the study, compared with approximately 2% to 5%in the rest of the U.S.

The team also found that people who were living in minority neighborhoods or self-identified as being minorities were at an approximately two-to threefold higher risk at that time for seroprevalence and infection. As Anand concludes, “It wasn’t just that they were getting COVID-19 at the same rate and dying more. It was also that they were getting more COVID-19.”

And within these results, they were able to extrapolate to larger regions, estimating that seroprevalence in the U.S. at the time would be somewhere near 9% for the U.S. adult population. This estimate, incidentally, ended up being remarkably accurate—at the time the Stanford study was published, the Centers for Disease Control and Prevention was conducting an independent analysis that hadn’t yet been completed, but when it was published in August, their estimates were “very similar.” Initially, Anand recalls, “it was important to understand in real time what was happening with the epidemic.” Ascend’s data drew from 46 states and a third of all counties in the U.S., spread from coast to coast.

Working With Industry

Anand called working with Ascend “mutually inspiring” because the company displayed an incredibly compassionate desire to help in any way. “They understood the true potential of what they had, and we really understood their willingness and capabilities as well,” Anand says.

Montez-Rath agrees: “What surprised me the most about this project was the people involved, especially Ascend’s participation.” She calls this industry/academy collaboration “something to be celebrated.”

Parsonnet was “very happy about how great the renal dialysis units were about wanting to participate.” She adds, “It’s nice to see these dialysis centers really care about doing the right thing for their patients. It makes me feel good about the world.”

Chertow concludes, “Academy and industry partnerships sometimes work!”

“We’re not developing vaccines, we’re not the people doing the phenomenal earth-shattering stuff, but we have helped to inform the understanding of where the pandemic was raging, how it’s been spreading, how it’s been disproportionately affecting persons of color and other disadvantaged populations. We’re helping, little by little, in our own way”

Future Studies

The pandemic will eventually end, but studies using this remnant blood are continuing, and projects with this population will continue in the future too. The Stanford team is examining various aspects of dialysis and COVID-19, including studying transmission risks and infection mitigation at dialysis centers and looking to the possibility of future seasonal COVID-19 infections and how they will affect dialysis patients, who often do worse during winter months.

They’re also working on a repeat cross section to try to get a sense of seroprevalence in the U.S. a year into the pandemic, particularly before the vaccine rollout—information that Anand calls “critical.” In addition, they have both vaccine response and vaccine acceptability studies in dialysis patients in the works, including a vaccine acceptability survey among dialysis patients led by nephrology fellow Pablo Garcia, MD.

And their work has even helped inspire other universities and dialysis centers. “I know several dialysis networks are looking at vaccine response in dialysis patients,” Anand says. “They may have chosen to do that independently, but hopefully we gave them sort of a road map for how to do it as well. Which is great, because we want our patients to be protected, and we want our colleagues to study that and improve ways to make that happen.”

Part of the Fight

Chertow concludes, “I think in our own way we’ve contributed to the fight against COVID-19. We’re not developing vaccines, we’re not the people doing the phenomenal earth-shattering stuff, but we have helped to inform the understanding of where the pandemic was raging, how it’s been spreading, how it’s been disproportionately affecting persons of color and other disadvantaged populations. We’re helping, little by little, in our own way.”

Jialin Han, MS

Working Within and Among Divisions

The team members also enjoyed working among different divisions at Stanford. Han appreciated the learning opportunities the work gave him. “One of the amazing parts about being a biostatistician is that I can work with people from different backgrounds and disciplines, and I really enjoy it,” he says.

Anand loved working with Parsonnet. “She’s one of the world’s experts on epidemiology in general, and just getting her perspective on contextualization for how this work would be important and why it would be important was really great,” she says.

And Parsonnet also loved the team. “Shuchi is amazing, really sharp and hardworking and innovative and really tremendous,” she says. “And Maria is just terrific in thinking about ways to look at the data. I think of it as their work, and it was an honor for me to be able to participate in any way.”

Chertow, too, was filled with enthusiasm for the team, from Ascend and all across Stanford. “It’s been a very meaningful and satisfying collaboration for me,” he states. “The greatest gift to a teacher is when his or her student proves to be 10 times smarter than he is. It’s sort of like planting a seed and watching a grove of fruit-bearing trees grow. And that’s what working with people like Shuchi and Maria and Julie has been like.”