Yue (June) Jiao

Strategic Analytics Operations Lead

Yue (June) Jiao

Yue (June) Jiao, Ph.D., is a Senior Principal Analytics Project Manager at the Renal Research Institute (RRI). She holds a Ph.D. in Operations Research from Kansas State University, USA, as well as a Master’s and a bachelor’s degree in Automation from Tsinghua University, Beijing, China. With over 20 years of experience, she specializes in statistical analytics, predictive modeling, simulation and optimization, pattern recognition and control, image processing, and database design and management.

Yue has contributed to healthcare quality improvement research through the Clinical Advanced Analytics division of the Global Medical Office at Fresenius Medical Care. Her work includes developing and implementing predictive models, supporting interdisciplinary team interventions, and providing operational support to clinics. She plays a critical role in the design, development, operationalization, and ongoing management of ApolloDialDb, the world’s largest fully anonymized global dialysis dataset, as well as the MONDO (MONitoring Dialysis Outcomes) Initiative, coordinated by RRI and managed by Fresenius Medical Care.

Before joining the company, Yue held a research position at the University of Massachusetts, where she applied advanced modeling, simulation, and optimization techniques to study fish population dynamics, optimize sampling designs, and develop decision support systems for fisheries management.

Contact Information:

Recent Articles by Yue (June) Jiao

  • Peritoneal dialysis international
    January 20, 2026
    Anemia-independent prognostic value of iron deficiency in incident peritoneal dialysis patients
    Vladimir Rigodon, Murilo Guedes, Peter G Pecoits, Brianna Hartley, Yue Jiao, Len A Usvyat, Dinesh K Chatoth, Jeffrey L Hymes, Franklin W Maddux, Jeroen Kooman, Thyago P Moraes, Jochen G Raimann, Peter Kotanko, John W Larkin, Roberto Pecoits-Filho
    Background and objectivesIron plays a critical role beyond erythropoiesis, yet the prognostic significance of iron deficiency (ID) independent of anemia remains poorly defined in the peritoneal dialysis (PD) population. This study aimed to evaluate the association between iron status, specifically transferrin saturation (TSAT), and mortality in PD patients, independent of hemoglobin levels.Design, setting, participants, and measurementsWe conducted a retrospective cohort study of 11,013 adults who initiated PD at a large US dialysis network between December 2004 and January 2011. Patients had at least 180 days on PD and baseline data on TSAT, ferritin, hemoglobin, albumin, and white blood cell count. The primary outcome was all-cause mortality. Broadly adjusted associations between iron parameters and mortality were assessed using Cox proportional hazards models and restricted cubic splines, with adjustments for demographic, clinical, treatment-related, and laboratory variables including hemoglobin and ESA use.ResultsIron deficiency, defined as TSAT ≤20%, was present in 10% of patients at PD initiation. The cohort was 54% male and 70% Caucasian, with a mean age of 55 years; 39% had diabetes. While 91% received erythropoiesis-stimulating agents, only 34% received IV iron. After comprehensive adjustment, TSAT ≤20% remained independently associated with increased mortality (adjusted HR: 1.26; 95% CI: 1.12-1.42). Spline analyses showed a sharp rise in mortality risk at TSAT levels below 25%. Ferritin was inconsistently associated with mortality risk. During follow-up, 2704 deaths occurred (24.6% of the cohort) over a median 440-day follow-up.ConclusionsIron deficiency is common in incident PD patients and is associated with increased mortality risk, independent of anemia. These findings challenge current anemia-centric treatment paradigms and suggest that iron status, particularly TSAT, should be routinely assessed in PD patients regardless of hemoglobin levels. A prospective, randomized trial is warranted to evaluate whether proactive iron management improves outcomes in this population.
  • Kidney international reports
    September 9, 2025
    Creating a Globally Distributed Multinational Dialysis Database - The ApolloDialDb Initiative
    Melanie Wolf, Yue Jiao, Kaitlyn Croft, Carly Hahn Contino, Justin Zimbelman, Kanti Singh, Mitesh Soni, Andrew Dickinson, Jeroen P Kooman, Dinesh Chatoth, Adrian Guinsburg, Stefano Stuard, Milind Nikam, Michelle Carver, Len Usvyat, Franklin W Maddux, Sheetal Chaudhuri, John Larkin
    RESULTSApollo captures data from January 2018 to March 2021 from 40 countries and 543,169 patients worldwide (4.6% in Asia-Pacific [AP], 13.9% in Europe, Middle East, and Africa [EMEA], 7.0% in Latin America [LA], and 74.5% in North America [NA]). It contains demographic data, 35,874,039 laboratory, and 140,016,249 treatment observations as well as frequently recorded medication information, and clinical outcomes (e.g., hospitalization and mortality). Several regional differences can be observed using these data, such as age, treatment modality, and treatment time.CONCLUSIONCreating a robust multinational dialysis database offers vast opportunities to conduct real-world research and data analytics, including the development of artificial intelligence models. These activities hold promise of advancing the understanding of kidney disease and dialysis therapies. It can serve as comparative resource for the nephrology community.INTRODUCTIONLarge amounts of data are captured during dialysis, yet multinational datasets are scarce because of challenges in harmonizing and integrating clinical data, as well as complying with data protection regulations across the world. A global kidney care provider, Fresenius Medical Care, approached this challenge and finalized the creation of an anonymized dialysis database, coined ApolloDialDb (Apollo). We report on the approach used for database creation and detail dialysis patient characteristics globally.METHODSTo create this globally distributed multinational database, data from different electronic clinical systems were extracted, covering routinely collected medical information from dialysis clinics worldwide. This data were harmonized, and then anonymized following a reidentification risk assessment conducted by the external company Privacy Analytics, Ontario, Canada. The data was consolidated and is stored in a central cloud environment and will be updated periodically.