Maximising Organ Donor Utility System-wide (MODUS): A study protocol for using linked health services data in multi-modal modelling of kidney transplant waitlist outcomes

Maximising Organ Donor Utility System-wide (MODUS): A study protocol for using linked health services data in multi-modal modelling of kidney transplant waitlist outcomes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Maximising Organ Donor Utility System-wide (MODUS): A study protocol for using linked health services data in multi-modal modelling of kidney transplant waitlist outcomes Brenda Maria Rosales, Karan K Shah, Nicole La Mata, Heather Baldwin, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4628090/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Increasing deceased organ donation is a global priority constrained by concerns of inadvertent transmission of cancer or infectious disease from deceased organ donors. Up to 60% of potential donors referred for consideration for deceased organ donation in Australia do not proceed for biovigilance concerns. However, there are opportunities to increase acceptance. We aim to describe the impact of accepting or declining potential donors forgone for biovigilance concerns on patient and transplant outcomes. We will use data for all potential donors referred for consideration for deceased organ donation and data for patients ever waitlisted for kidney transplantation in New South Wales, Australia’s most populous state, 2010–2020. We will 1) describe the patient journey on the kidney transplant waitlist, including episodes of suspension and reactivation, time waiting and whether transplanted; 2) describe the characteristics of patients on the kidney transplant waitlist who decline a deceased donor organ offer and patient outcomes after their first decline; 3) determine potential gains made through increased donor acceptance and profile potential donors forgone for medical suitability; 4) use economic modelling to investigate the benefits and costs of increasing donor acceptance. Research findings will be presented at scientific conferences, published in the scientific media, and via collaborator networks. Kidney Failure Transplant Waitlist Organ Allocation Biovigilance Population-based study Health Economic Evaluation Figures Figure 1 Figure 2 Figure 3 1. Introduction Kidney failure is a leading cause of morbidity and mortality. Globally, the number of people on dialysis or with a kidney transplant has more than doubled since 1990(Lysaght 2002 ). In 2010, over 4.9 million people had kidney failure worldwide, of which 2.6 million were on dialysis or had a kidney transplant(Liyanage et al. 2015 ). Kidney transplantation is the preferred treatment for kidney failure as it increases patient survival, improves quality of life and is more cost-effective than dialysis, making it a compelling option for those who are suitable(Webster et al. 2017 ). In Australia, kidney transplantation rates have steadily increased; despite this, demand continues to outweigh donor supply (Wyld, Wyburn, and Chadban 2021 ). Increasing opportunities for kidney transplantation through deceased organ donation is, therefore, a global and national priority(Australian Organ and Tissue Donation and Transplantation Authority 2021 ). To access a deceased donor kidney transplant in Australia, people on dialysis must be assessed as eligible for transplantation to enter the deceased donor waitlist(The Transplantation Society of Australia and New Zealand 2023 ). Potential transplant recipients must understand and accept inherent risks from the procedure and ongoing treatment and have a high likelihood of significant benefit from transplantation to be eligible. Risk-benefit assessments are conducted by a multidisciplinary team that reviews clinical and surgical factors, mental health, social circumstances, and impacts. Any significant risk of death from comorbidity (e.g. heart disease, cancer, infection) is a contraindication for transplant and patients will not be eligible for the deceased donor waitlist. When a donor kidney becomes available, all waitlisted patients are considered by the national organ allocation algorithm, designed to find an immunologically compatible match, whilst also prioritising those who have waited longest or who are under 18 years. The algorithm stratifies matches by blood group and balances time spent waiting with the degree of donor-recipient matching nationally and by state of donor origin to generate a list of potential donor-recipient pairs in ranked order. In Australia, time spent waiting is measured from initiation of dialysis to account for delays in reaching the active waiting list due to medical issues or delayed transplant suitability assessment, and to ensure the sense of fairness prioritised by consumers(Chapman and Kanellis 2018 ; The Transplantation Society of Australia and New Zealand 2019). At the end of 2019, there were 1,100 Australians on the deceased donor kidney transplant waitlist, with a median wait-time of 1–4 years and a transplant rate of 7 per 100 years on dialysis(Wyld, Wyburn, and Chadban 2021 ). Prior research has focused on factors impacting access to the waiting list or transplantation and subsequent post-transplant health outcomes(Khanal et al. 2018 ; Sypek et al. 2019 ; Talamantes et al. 2017 ). However, the time spent waiting is under-explored. Kidney transplant waitlists are dynamic and change daily as new people are added, and existing people are transplanted or become unwell and so are temporarily or permanently removed from the waitlist, or die while waiting(ANZDATA Registry 2020 ). Patients can enter a variety of clinical states after being initiated onto the waitlist, impacting their experiences. Intercurrent illness, surgery, or investigations may necessitate temporary suspension or permanent removal from the waiting list. It has not been described how events occurring after waitlisting impact equitable access to transplantation. In 2009, The Australian Government established a national program to increase capability and capacity within the health system to maximise organ donation rates(Australian Organ and Tissue Donation and Transplantation Authority 2021 ). Since 2009, the number of deceased organ donors has more than doubled in Australia(Australian Organ and Tissue Donation and Transplantation Authority 2021 ). Deceased organ donation is coordinated by the Organ and Tissue Authority, who devolve to a national network of state-based donation specialist agencies called Organ and Tissue Donation Services (OTDS). In Australia, New South Wales (NSW) has a greatest number of people waiting for a kidney transplant than other states and territories, and a more complex service delivery compared to other jurisdictions. Where some states have one kidney transplanting centre, NSW has eight. Potential donors are identified by NSW hospitals and referred to NSW OTDS for consideration for deceased organ donation (Fig. 1 ). Donation specialist coordinates the thorough investigation, including medical history and assessment of their medical suitability for donation, whilst also seeking consent for a donation from next-of-kin. Potential donors who meet medical suitability criteria and have consenting next-of-kin (intended donors) enter the national allocation algorithm to be matched with kidney transplant candidates. Those who undergo surgery for organ retrieval are considered actual donors, even if their organs are not eventually transplanted. Improvements in donation rates in Australia have occurred unevenly. NSW has the greatest number of donors each year nationally. However, donation rates have not improved as much as other states when standardised for population size (Fig. 2 ). Furthermore, despite significant increases in potential donors referred to NSW OTDS, our prior work has shown that the proportion of actual donors has increased at a much slower rate (Fig. 3 ). Nationally, fewer than 42% of potential donors proceeded to actual donations in 2020(Australian Organ and Tissue Donation and Transplantation Authority 2021 ). In NSW, only 22% of potential donors proceed to actual donation(Thomson et al. 2019). Improving donation in NSW, Australia’s most populous state, would greatly impact national donation levels and outcomes for people on the waitlist for kidney transplants. Preventing transmission of donor-derived infectious diseases or cancer (biovigilance) is a central concern in transplant programs. Donor medical suitability assessment is based on the perception of the biovigilance risk a donor poses. Evidence of infectious disease, a current or historic malignancy, and behaviours that increase the risk of blood-borne viruses is often obtained indirectly from hospital records, primary care records, family members or friends. There is varied access to past medical records and limited possibilities to confirm risk within the donor assessment time frame for deceased donors. In this context, the actual risk of disease transmission may be unconfirmed, and transplant clinicians make recommendations and decisions under conditions of uncertainty. Donation decisions for deceased donor organs are time-sensitive and may vary among clinicians. We have demonstrated previously that even when clinicians correctly interpret clinical information related to biovigilance, their recommendations of donor suitability may be inconsistent(Waller et al. 2018 ). Furthermore, many of the surveyed clinicians were found to be risk averse when making donor decisions for their patients, even when blood-borne virus risk of transmission from donor to potential recipient was < 1:10,000(Waller et al. 2018 ). Further opportunities exist to increase the deceased donor pool among those currently excluded due to biovigilance concerns. Our prior work has identified several potential missed opportunities for deceased organ donation in NSW. Of over 3,000 potential donors referred between 2010–2015, approximately 10% had increased-risk behaviours for blood-borne viruses (hepatitis B, C and HIV), but the majority were deemed not medically suitable for organ donation without specific testing to confirm or refute virus exposure(Waller et al. 2021 ). Those potential donors who were tested showed a < 1 in 100,000 risk of having the disease. Similarly, 29% of potential donors that were deemed not medically suitable due to their perceived risk of cancer transmission had a tumour with low risk of transmission when verified by cancer registry records and the use of their organs for transplantation would have been within clinical transplantation guidelines(Hedley et al. 2022 ). The inclusion of potential deceased organ donors with a low risk of disease transmission but currently foregone as donors, may increase the donor pool and opportunities for transplantation. However, the potential impact of such practice changes, and downstream impact on the kidney transplant waitlist, patient outcomes, and healthcare costs are unknown. In this study, we aim to investigate whether a new policy of increasing donor acceptance can increase access to donor kidneys for people with kidney failure in four related projects: Kidney waitlist dynamics : Using bi-national individual-level data, we will describe and evaluate factors impacting the current patient journey on the kidney transplant waitlist, including all clinical transitions: suspension and reactivation, death before transplant, and transplantation. Describing the impact of donor decline for patients on the kidney waitlist : Using our linked data as the cohort study platform, we will use flexible parametric survival models, to quantify the time from decline to deceased donor transplantation and impact of intersectional disadvantage on waiting time after decline of offer for patients on the kidney transplant waitlist. Deceased donor profiling : Using our linked data as the cohort study platform, we will describe donor referral risk profiles and determine any potential donor gains that could be made through better access to donor information at the time of decision-making, more accurate estimation of absolute biovigilance risk and, varying the acceptable biovigilance risk thresholds for accepting donors. Economic modelling of increased donor acceptance : Using health economic models (cohort and individual patient level simulations), we will quantify the impact of varying donor referral decisions on healthcare costs, health benefits (quality-adjusted survival) and efficiency measures (time on waitlist and time to a kidney transplant). 2. Methods and analysis 2.1 Consumer engagement : The MODUS study has been designed with input from peak consumer organisations and key stakeholders in delivery of Australia's organ donation and transplantation service. Our research partners have been integral to the development of this study protocol; the NSW Ministry of Health has underwritten the Biovigilance Public Health Register and will contribute to outcome development, and the NSW Organ and Tissue Donation Service will contribute expertise and help fidelity through close relationship with medical suitability advisors and transplanting hospitals; Kidney Health Australia has provided and ongoing vital consumer liaison. Increasing opportunities for transplantation is a priority for people with kidney disease. Our consumer liaisons will advise on project development, interpretation of results and dissemination strategies for research findings. 2.2 Study design and population : To profile donors, we will use an established dataset that contains outcome data for all candidates for deceased organ donors referred to NSW OTDS 2010–2020, including those that proceeded to donation (actual donors), were deemed suitable for donation but never proceeded (intended donors) and were foregone for medical unsuitability (potential donors forgone)(Thomson et al. 2019). The data in our outcome models will be based on all people who entered the kidney waitlist for their first transplant between 1st July 2010 and 31st Dec 2019 in NSW from the Australian and New Zealand Dialysis and Transplantation Registry (ANZDATA) and OrganMatch. ANZDATA is a collaborative disease registry collecting clinical and treatment information on people undergoing dialysis or transplants for kidney failure from all treatment centres in Australia and New Zealand since 1977. OrganMatch is a clinical transplant system that facilitates compatibility matching of recipients and donors for organ transplantation and maintains the kidney transplant waiting list. We will exclude those who had multi-organ transplants (e.g., kidney + pancreas). Our study follow-up will be from waitlist entry until death, or 31st Dec 2019. 2.3 Outcomes measured : Aims 1 and 2 will measure outcomes in patients ever waitlisted for kidney transplantation, including time from waitlist entry to deceased donor transplant; clinical transitions after waitlist entry, such as removal from waitlist (i.e. temporary suspension and permanent) or death before transplant, number of deceased donor organ offers made and, probability of receiving a deceased donor transplant. Aim 3 will describe and categorise the reasons for medical unsuitability, donor quality, and potential donor numbers using current acceptance criteria. Aim 4 will measure the cost-effectiveness of increasing deceased donor acceptance using current guidelines, with health outcomes quantified using quality-adjusted life years (QALY) and costs measured in Australian dollars. 2.4 Analysis : Separate analyses will be conducted to meet each study's aim. 2.4.1 Deceased donor profiling : We will investigate potential donors forgone who were deemed not medically suitable in NSW. Specifically, we will summarise demographic and clinical characteristics, including age, sex, blood group, comorbidities and calculated Australian kidney donor profile index (KDPI), of all consented potential donors and compare those declared medically unsuitable for donation with those that did proceed to donation. We will summarise the reasons given for why these potential donors did not proceed to donate, including where there were multiple reasons. Lastly, we will determine the proportion of potential donors forgone because of concerns around medical suitability, who were of better or the same quality as those who proceeded to donate, overall and by calendar year. 2.4.2 Kidney waitlist dynamics : We will build a multi-state model of the kidney transplant waitlist and use this to describe kidney waitlist dynamics and evaluate all clinical transitions after entering the kidney waitlist. Clinical states will include active on the waitlist, temporary suspension, permanent removal, kidney transplant (deceased donor, living donor and paired kidney exchange donor), and death before transplant. We will exclude people who were already active on the waitlist (i.e., prevalent cases). Post-transplant clinical states will include graft failure, return to dialysis and re-entry to waitlist for subsequent transplant. We will use Markov models to evaluate patient factors associated with transitions after waitlist entry. Patient factors of interest include sex, age at waitlist entry, ethnicity, comorbidity burden and cause of kidney failure. Specifically, we will estimate transition intensity hazard ratios to indicate whether a transition is more or less likely to occur based on patient factors. Transitions of particular interest include from waitlist entry to suspension, suspension to waitlist (active), suspension to death before transplant, and waitlist entry to transplant. 2.4.3 Describing the impact of donor decline for patients on the kidney waitlist : We will investigate patients who entered the kidney transplant waiting list in NSW from 2010–2020. We will use records of ranked offers for every actual donor against potential recipients. Using records of which donor-recipient pairs were accepted, we will understand which donor-recipient pairs were offered but declined by transplant teams. We will estimate decline rates of the first donor-recipient paired offer by recipient characteristics, including blood group, sex, age, ethnicity, immunological sensitisation (PRA), and comorbidities. Subsequent outcomes after the decline of the first offer will be examined, including time to the next offer, time to the next better offer (measured as next donor offer with improved KDPI), number of offers to transplant if transplanted, rate and duration of time spent suspended from the list, receiving a transplant (deceased or living donor), and death. Time from decline to transplantation will be examined, by patient characteristics, using Kaplan-Meier curves and restricted mean survival time. We will use flexible parametric survival models to examine the time from decline to deceased donor transplantation for patients with different characteristics and to make adjusted predictions on time from decline to transplantation, evaluating impact of intersectional disadvantage for patients with different sociodemographic and clinical characteristics. Finally, we will assess whether the decline of the offer leads to the subsequent transplant of a better quality kidney; KDPIs of declined kidneys will be compared to accepted kidneys using the sign test for matched pairs. 2.4.4 Economic Modelling of Increased Donor Acceptance : We will use cohort and individual-level simulation-based Markov models to compare the cost-effectiveness of the shift in clinical practice that encourages increased utilisation of potential donors with specific biovigilance concerns but who are within current guidelines (e.g., history of cancer or increased risk of infectious disease, including blood-borne virus) in the Australian healthcare setting. Biovigilance risk thresholds for acceptance of deceased organ donors will follow current clinical guidelines(The Transplantation Society of Australia and New Zealand 2019, 2023 ). Health states included in our analysis include: being active on the transplant waitlist, being suspended from the waitlist, having a functioning kidney transplant, transplant failure and return to dialysis, death from kidney failure, and death from other causes, as well as health states specific to cancer or blood-borne viruses. The transition of kidney patients through different health states over a lifetime time horizon, will be simulated based on transition probabilities over 3-month time periods (Markov cycles). Health outcomes will be measured in terms of life-years gained and quality-adjusted life years (QALYs) gained, which incorporates both length and quality-of-life (scale 0–1, where 0 = death and 1 = full health). Costs will be measured in Australian dollars using data obtained from the Medicare Benefits Schedule (MBS), Pharmaceutical Benefits Scheme (PBS), and relevant unit pricing based on Australian-Refined Diagnosis Related Group (AR-DRG) codes and the Independent Hospital Pricing Authority (IHPA) Net Efficient Price (NEP). A discount factor of 5% per year will be applied to costs and health outcomes, as per Australian government recommendations(Pharmaceutical Benefits Advisory Committee (PBAC) 2016 ; Medical Services Advisory Committee (MSAC) 2021 ). The cost-effectiveness of the shift in clinical practice to accept deceased donor organs with varying biovigilance risks, risk of cancer and blood-borne virus transmission aligned with current guidelines will be compared with the current practice, where these donors are typically declined. Cost-effectiveness will be measured as a ratio of incremental costs to incremental QALYs expressed as an incremental cost-effectiveness ratio (ICER) or net monetary benefit. A willingness to pay threshold will be determined based on estimates from the literature per QALY gained and used to interpret the ICER. A strategy will be interpreted as cost-effective if the ICER is less than the willingness to pay threshold per QALY gained. Sensitivity analyses will be conducted using varying willingness to pay thresholds. We will use individual-level simulation models to overcome some of the limitations of cohort-based Markov models, as well as to incorporate individual recipient and donor characteristics(Karnon and Haji Ali Afzali 2014 ; Briggs et al. 2016 ). Recipient-level characteristics such as age, sex, blood group, number of previous kidney transplants, dialysis vintage, comorbidities, and donor characteristics such as age, sex, donor type (donation by brain or circulatory death), and Australian KDPI will be used. We plan to undertake a Distributional Cost-Effectiveness Analysis, a framework to incorporate health inequality impacts into the cost-effectiveness analysis comparing shifts in the clinical practice to accept deceased organ donors with increased risk of cancer and blood-borne virus transmission with current practice where these donors are typically declined(Cookson et al. 2021 ). The model structure and analyses will follow best practice modelling guidelines from the International Society for Pharmacoeconomics and Outcomes Research(International Society for Pharmacoeconomics and Outcomes Research 2018 ). Comprehensive deterministic and probabilistic sensitivity analyses will be conducted to account for all parameter uncertainty in the models. Analyses will be performed using STATA, R and TreeAGE software. 2.5 Expected Outcomes : MODUS will provide evidence of the individual-level and health service effects of increasing acceptance of deceased donor kidneys that would otherwise be declined due to biovigilance concerns. Specifically, we expect to report our findings on 1) improvements in overall patient survival (life-years gained) and 2) quality of life (QALYs gained) by increasing the number of wait-listed people transplanted from donors with acceptable biovigilance risk who are currently foregone. We will also report on 3) any reductions in mortality while on the kidney waitlist, 4) any increases in disease transmission, and 5) the cost-effectiveness of a potential “informed biovigilance strategy” versus current practice. 3. Discussion Increasing the number of deceased organ donors available for transplantation is a global priority, but it is constrained by concerns of inadvertent transmission of cancer or infectious disease from deceased organ donors. Up to 60% of people referred for consideration for deceased organ donation in Australia do not proceed because of these concerns. However, we previously found opportunities to increase donation rates. In this work, we aim to describe how accepting or declining potential donors who did not proceed because of unfounded concerns around disease transmission will impact transplant recipients. Our work will quantify the potential value of system change in terms of gains in survival and quality of life for people with kidney failure waiting for a transplant who would otherwise have remained waiting. In doing so, we will develop evidence to support policy and complex clinical decisions in Australia's organ donor referral process with potential global application. Our partner organisations will provide organisational structure and policy pathways to ensure sustainable knowledge transfer and implementation of MODUS findings. Declarations Dissemination of findings: The results of MODUS - Modelling will be reported back to study CIs, AIs and all stakeholders including the NSW Ministry of Health, and consumers. Research findings will be presented at national and international professional network conferences and published in the scientific media. Publications will be led by study CIs, listed above, with acknowledgement of authorship to the relevant study members with expertise in the field, and consumes who significantly contributed to the development, analysis and translation of the study. Authors’ contributions: BMR and KS contributed equally as the first authors of this manuscript. ACW and RLM were responsible for the conception and design of the MODUS Modelling study and the initiation of stakeholder collaborations. NDM, JB, and JH provided expertise in developing the described statistical analysis plans and data requirements. AR is a consumer co-author and has provided their perspective on idea generation and study conception. AR, PC, MW, KW and PK provided expertise on the manuscript, study design and critical intellectual content. This work has been published on behalf of the MODUS Study Group: Professor Kirsten McCaffery, Dr Danielle Muscat, Prof Claire Vajdic, Dr Elena Cavazzoni, Prof Henry Pleass, Prof Nicholas Cross, Ms Rhonda Holdsworth, Prof Shilpanjali Jesudason and Prof William Rawlinson. Ethics approval : This study was approved by the University of Sydney Human Research Ethics Committee (Project No.: 2020/828). Consent to participate and publish : Linked patient health data was collated as a NSW Public Health Register under the Public Health Act, NSW 2010. Individual consent was waivered under the common public good. De-identified patient data was used for analysis. Participating institutions were all kidney dialysis and transplant centers in Australia and New Zealand that report to the Australian and New Zealand Dialysis and Transplant Registry (ANZDATA). No organs/tissues were obtained from prisoners in this study. Data availability : The data collated for this study is under the management of the NSW Ministry of Health as a Public Health Register. Summary-level data may be provided with appropriate permissions. Funding statement : This work was supported by the Australian National Health and Medical Research Council (NHMRC) Partnership Project grant (ID APP1171364). This support is in partnership with the NSW Ministry of Health, Office of the Chair, Kidney Health Australia and the NSW Organ and Tissue Donation Service. Competing interests ’ statement : The study investigators have no competing interests. All study members have declared all financial and nonfinancial affiliations to the HREC committee in the original ethics application. Acknowledgements: The data reported here have been supplied by the NSW Organ and Tissue Donation Service and the Australia and New Zealand Dialysis and Transplant Registry. The interpretation and reporting of these data are the responsibility of the authors and in no way should be seen as an official policy or interpretation of ANDATA or NSW OTDS. This work was funded by an Australian National Health and Medical Research Council Partnership Grant (#1171364). This support is in partnership with the NSW Ministry of Health, Office of the Chair, Kidney Health Australia and the NSW Organ and Tissue Donation Service. References ANZDATA Registry: Chapter 6: Australian Transplant Waiting List. In 43rd Report , edited by Australia and New Zealand Dialysis and Transplant Registry. Adelaide, Australia. (2020) Australian Organ and Tissue Donation and Transplantation Authority: Organ and Tissue Authority 2020–21 Annual Report. In, edited by Australian Government Department of Health. 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Nephrol. 12 , 483–492 (2017) The Transplantation Society of Australia and New Zealand: Clinical guidelines for organ transplantation from deceased donors. In, edited by Australian Organ and Tissue Authority. Canberra, Australia: The Transplantation Society of Australia and New Zealand. (2023) Thomson, I.K., Rosales, B.M., Kelly, P.J., Wyburn, K., Waller, K.M.J., Hirsch, D., O'Leary, M.J.: and A. C. Webster. 2019. 'Epidemiology and Comorbidity Burden of Organ Donor Referrals in Australia: Cohort Study 2010–2015'. Transplantation direct, 5 : e504 Waller, K.M.J., De La Mata, N.L., Rosales, B.M., Hedley, J.A., Kelly, P.J., Thomson, I.K., O'Leary, M.J., Cavazzoni, E., Ramachandran, V., Rawlinson, W.D., Wyburn, K.R., Webster, A.C.: 'Characteristics and Donation Outcomes of Potential Organ Donors Perceived to be at Increased Risk for Blood Borne Virus Transmission: an Australian Cohort Study 2010–2018', Transplantation . (2021) Waller, K.M.J., Wyburn, K.R., Shackel, N.A., O'Leary, M.J., Kelly, P.J., Webster, A.C.: 'Hepatitis Transmission Risk in Kidney Transplantation (the HINT study): A Cross-Sectional Survey of Transplant Clinicians in Australia and New Zealand', Transplantation , 102: 146 – 53. (2018) Webster, A.C., Nagler, E.V., Morton, R.L., Masson, P.: Lancet. 389 , 1238–1252 (2017). 'Chronic Kidney Disease' Wyld, M.L.R., Wyburn, K.R., Chadban, S.J.: 'Global Perspective on Kidney Transplantation: Australia', Kidney360 , 2: 1641-44. (2021) Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Rosales","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABLklEQVRIie2Rv2qDUBSHTyrY5aauEQntI9wgmAoSXyUi2MXSQpcOHZzs0jpHSN/BvMGVC3GRZhWyCIVOEpwkUGl7QpYWlKZboX7D/cf5OJffAejo+IPQ3UL25x4DMHCf7m/eAQqg4vxe4T8rY4Uv8+IOriSJ56ysVyZNLuMXAsYwYsLroEHRA+diNF+CHs4cGof+2orSja0ScNSIiVqTQlOiKUQESjOgvO+tpzRz8QW4FTFoUaRKIe+orJKS1/Wzicr4jcAHKsdVSxdR6fuoMJdyEFkvwi4CAYYKaeyiP4ia/BQMqDxzr+NH37bCtFDlObXVkJOb86bECMZSVAaVpGSRb+uJeZK4o7K4nQyD5H6RtQSNfPnAGQM4Irt5Ce313zn1cIzbQ6s7Ojo6/gOfjEpoy3tFYgIAAAAASUVORK5CYII=","orcid":"","institution":"University of Sydney","correspondingAuthor":true,"prefix":"","firstName":"Brenda","middleName":"Maria","lastName":"Rosales","suffix":""},{"id":323551886,"identity":"4e36a9ad-4db2-4f9c-be96-d82c4b4dffd6","order_by":1,"name":"Karan K Shah","email":"","orcid":"","institution":"University of 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Sydney","correspondingAuthor":false,"prefix":"","firstName":"James","middleName":"A","lastName":"Hedley","suffix":""},{"id":323551890,"identity":"24646f12-d21c-4c34-8e05-0677da307af2","order_by":5,"name":"Philip Clayton","email":"","orcid":"","institution":"Australia and New Zealand Dialysis and Transplant Registry","correspondingAuthor":false,"prefix":"","firstName":"Philip","middleName":"","lastName":"Clayton","suffix":""},{"id":323551891,"identity":"530ac3cc-36a4-4a51-a4f1-6ba6251d5b69","order_by":6,"name":"Melanie Wyld","email":"","orcid":"","institution":"University of Sydney","correspondingAuthor":false,"prefix":"","firstName":"Melanie","middleName":"","lastName":"Wyld","suffix":""},{"id":323551892,"identity":"7e14c7d7-434d-481d-bd73-2d9b436f0876","order_by":7,"name":"Kate Wyburn","email":"","orcid":"","institution":"Royal Prince Alfred Hospital","correspondingAuthor":false,"prefix":"","firstName":"Kate","middleName":"","lastName":"Wyburn","suffix":""},{"id":323551893,"identity":"9499ce00-dbbe-438f-a84d-35b1432458d9","order_by":8,"name":"Patrick J Kelly","email":"","orcid":"","institution":"University of Sydney","correspondingAuthor":false,"prefix":"","firstName":"Patrick","middleName":"J","lastName":"Kelly","suffix":""},{"id":323551894,"identity":"8ea12d5a-dbf1-4916-ba91-261c962f5e61","order_by":9,"name":"Rachael L Morton","email":"","orcid":"","institution":"University of Sydney","correspondingAuthor":false,"prefix":"","firstName":"Rachael","middleName":"L","lastName":"Morton","suffix":""},{"id":323551895,"identity":"aa215a60-5717-48af-a42d-1da3397e96ff","order_by":10,"name":"Angela C Webster","email":"","orcid":"","institution":"University of Sydney","correspondingAuthor":false,"prefix":"","firstName":"Angela","middleName":"C","lastName":"Webster","suffix":""}],"badges":[],"createdAt":"2024-06-24 06:59:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4628090/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4628090/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":60597275,"identity":"5dfdb5da-bbe8-48dd-9b03-598f60765df0","added_by":"auto","created_at":"2024-07-18 15:48:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2114910,"visible":true,"origin":"","legend":"\u003cp\u003eSchema of the NSW deceased organ donor referral process(Collaborative Centre for Organ Donation Evidence 2020)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFootnote. \u003c/strong\u003ePotential donors referred to the NSW Organ and Tissue Donation Service who meet medical suitability criteria and who have consenting next-of-kin (intended donors) enter the national allocation algorithm to be matched with kidney transplant candidates. Those who do not meet medical suitability criteria or who were not accepted by transplant centres are considered potential donors forgone. Those whose organs are retrieved are considered actual donors.\u003c/p\u003e","description":"","filename":"fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-4628090/v1/30bfa9b77da4548fa1e71fac.png"},{"id":60596393,"identity":"a6ee2845-3e78-4f43-a4cb-eb705c373e9b","added_by":"auto","created_at":"2024-07-18 15:40:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1358253,"visible":true,"origin":"","legend":"\u003cp\u003eKidney deceased organ donor activity by Australian state over time, per million population, 2012-2023(Collaborative Centre for Organ Donation Evidence 2020)\u003c/p\u003e","description":"","filename":"fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-4628090/v1/49c3fef9337b8480428cc49e.png"},{"id":60596395,"identity":"c4f245b0-52bd-4bcb-94c1-cd1e013dc3fb","added_by":"auto","created_at":"2024-07-18 15:40:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":952006,"visible":true,"origin":"","legend":"\u003cp\u003eNumber of deceased organ donor referrals who proceeded (actual donors) vs the number referred to NSW Organ and Tissue Donation Service for consideration for donation (potential donors) in NSW, 2010-2022(Collaborative Centre for Organ Donation Evidence 2020)\u003c/p\u003e","description":"","filename":"fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-4628090/v1/128c0aff58c7b204387198e6.png"},{"id":60597285,"identity":"60c6c958-435e-4304-a8a7-f6270bd974e1","added_by":"auto","created_at":"2024-07-18 15:48:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5077273,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4628090/v1/eb01e6fb-f297-4367-92ee-489ee9745cb9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Maximising Organ Donor Utility System-wide (MODUS): A study protocol for using linked health services data in multi-modal modelling of kidney transplant waitlist outcomes","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eKidney failure is a leading cause of morbidity and mortality. Globally, the number of people on dialysis or with a kidney transplant has more than doubled since 1990(Lysaght \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). In 2010, over 4.9\u0026nbsp;million people had kidney failure worldwide, of which 2.6\u0026nbsp;million were on dialysis or had a kidney transplant(Liyanage et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Kidney transplantation is the preferred treatment for kidney failure as it increases patient survival, improves quality of life and is more cost-effective than dialysis, making it a compelling option for those who are suitable(Webster et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In Australia, kidney transplantation rates have steadily increased; despite this, demand continues to outweigh donor supply (Wyld, Wyburn, and Chadban \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Increasing opportunities for kidney transplantation through deceased organ donation is, therefore, a global and national priority(Australian Organ and Tissue Donation and Transplantation Authority \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo access a deceased donor kidney transplant in Australia, people on dialysis must be assessed as eligible for transplantation to enter the deceased donor waitlist(The Transplantation Society of Australia and New Zealand \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Potential transplant recipients must understand and accept inherent risks from the procedure and ongoing treatment and have a high likelihood of significant benefit from transplantation to be eligible. Risk-benefit assessments are conducted by a multidisciplinary team that reviews clinical and surgical factors, mental health, social circumstances, and impacts. Any significant risk of death from comorbidity (e.g. heart disease, cancer, infection) is a contraindication for transplant and patients will not be eligible for the deceased donor waitlist. When a donor kidney becomes available, all waitlisted patients are considered by the national organ allocation algorithm, designed to find an immunologically compatible match, whilst also prioritising those who have waited longest or who are under 18 years. The algorithm stratifies matches by blood group and balances time spent waiting with the degree of donor-recipient matching nationally and by state of donor origin to generate a list of potential donor-recipient pairs in ranked order. In Australia, time spent waiting is measured from initiation of dialysis to account for delays in reaching the active waiting list due to medical issues or delayed transplant suitability assessment, and to ensure the sense of fairness prioritised by consumers(Chapman and Kanellis \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; The Transplantation Society of Australia and New Zealand 2019). At the end of 2019, there were 1,100 Australians on the deceased donor kidney transplant waitlist, with a median wait-time of 1\u0026ndash;4 years and a transplant rate of 7 per 100 years on dialysis(Wyld, Wyburn, and Chadban \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePrior research has focused on factors impacting access to the waiting list or transplantation and subsequent post-transplant health outcomes(Khanal et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sypek et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Talamantes et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). However, the time spent waiting is under-explored. Kidney transplant waitlists are dynamic and change daily as new people are added, and existing people are transplanted or become unwell and so are temporarily or permanently removed from the waitlist, or die while waiting(ANZDATA Registry \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Patients can enter a variety of clinical states after being initiated onto the waitlist, impacting their experiences. Intercurrent illness, surgery, or investigations may necessitate temporary suspension or permanent removal from the waiting list. It has not been described how events occurring after waitlisting impact equitable access to transplantation.\u003c/p\u003e \u003cp\u003eIn 2009, The Australian Government established a national program to increase capability and capacity within the health system to maximise organ donation rates(Australian Organ and Tissue Donation and Transplantation Authority \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Since 2009, the number of deceased organ donors has more than doubled in Australia(Australian Organ and Tissue Donation and Transplantation Authority \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Deceased organ donation is coordinated by the Organ and Tissue Authority, who devolve to a national network of state-based donation specialist agencies called Organ and Tissue Donation Services (OTDS). In Australia, New South Wales (NSW) has a greatest number of people waiting for a kidney transplant than other states and territories, and a more complex service delivery compared to other jurisdictions. Where some states have one kidney transplanting centre, NSW has eight. Potential donors are identified by NSW hospitals and referred to NSW OTDS for consideration for deceased organ donation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Donation specialist coordinates the thorough investigation, including medical history and assessment of their medical suitability for donation, whilst also seeking consent for a donation from next-of-kin. Potential donors who meet medical suitability criteria and have consenting next-of-kin (intended donors) enter the national allocation algorithm to be matched with kidney transplant candidates. Those who undergo surgery for organ retrieval are considered actual donors, even if their organs are not eventually transplanted.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eImprovements in donation rates in Australia have occurred unevenly. NSW has the greatest number of donors each year nationally. However, donation rates have not improved as much as other states when standardised for population size (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Furthermore, despite significant increases in potential donors referred to NSW OTDS, our prior work has shown that the proportion of actual donors has increased at a much slower rate (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Nationally, fewer than 42% of potential donors proceeded to actual donations in 2020(Australian Organ and Tissue Donation and Transplantation Authority \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In NSW, only 22% of potential donors proceed to actual donation(Thomson et al. 2019). Improving donation in NSW, Australia\u0026rsquo;s most populous state, would greatly impact national donation levels and outcomes for people on the waitlist for kidney transplants.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePreventing transmission of donor-derived infectious diseases or cancer (biovigilance) is a central concern in transplant programs. Donor medical suitability assessment is based on the perception of the biovigilance risk a donor poses. Evidence of infectious disease, a current or historic malignancy, and behaviours that increase the risk of blood-borne viruses is often obtained indirectly from hospital records, primary care records, family members or friends. There is varied access to past medical records and limited possibilities to confirm risk within the donor assessment time frame for deceased donors. In this context, the actual risk of disease transmission may be unconfirmed, and transplant clinicians make recommendations and decisions under conditions of uncertainty. Donation decisions for deceased donor organs are time-sensitive and may vary among clinicians. We have demonstrated previously that even when clinicians correctly interpret clinical information related to biovigilance, their recommendations of donor suitability may be inconsistent(Waller et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Furthermore, many of the surveyed clinicians were found to be risk averse when making donor decisions for their patients, even when blood-borne virus risk of transmission from donor to potential recipient was \u0026lt;\u0026thinsp;1:10,000(Waller et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Further opportunities exist to increase the deceased donor pool among those currently excluded due to biovigilance concerns.\u003c/p\u003e \u003cp\u003eOur prior work has identified several potential missed opportunities for deceased organ donation in NSW. Of over 3,000 potential donors referred between 2010\u0026ndash;2015, approximately 10% had increased-risk behaviours for blood-borne viruses (hepatitis B, C and HIV), but the majority were deemed not medically suitable for organ donation without specific testing to confirm or refute virus exposure(Waller et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Those potential donors who were tested showed a\u0026thinsp;\u0026lt;\u0026thinsp;1 in 100,000 risk of having the disease. Similarly, 29% of potential donors that were deemed not medically suitable due to their perceived risk of cancer transmission had a tumour with low risk of transmission when verified by cancer registry records and the use of their organs for transplantation would have been within clinical transplantation guidelines(Hedley et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The inclusion of potential deceased organ donors with a low risk of disease transmission but currently foregone as donors, may increase the donor pool and opportunities for transplantation. However, the potential impact of such practice changes, and downstream impact on the kidney transplant waitlist, patient outcomes, and healthcare costs are unknown.\u003c/p\u003e \u003cp\u003eIn this study, we aim to investigate whether a new policy of increasing donor acceptance can increase access to donor kidneys for people with kidney failure in four related projects:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eKidney waitlist dynamics\u003c/em\u003e: Using bi-national individual-level data, we will describe and evaluate factors impacting the current patient journey on the kidney transplant waitlist, including all clinical transitions: suspension and reactivation, death before transplant, and transplantation.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eDescribing the impact of donor decline for patients on the kidney waitlist\u003c/em\u003e: Using our linked data as the cohort study platform, we will use flexible parametric survival models, to quantify the time from decline to deceased donor transplantation and impact of intersectional disadvantage on waiting time after decline of offer for patients on the kidney transplant waitlist.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eDeceased donor profiling\u003c/em\u003e: Using our linked data as the cohort study platform, we will describe donor referral risk profiles and determine any potential donor gains that could be made through better access to donor information at the time of decision-making, more accurate estimation of absolute biovigilance risk and, varying the acceptable biovigilance risk thresholds for accepting donors.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eEconomic modelling of increased donor acceptance\u003c/em\u003e: Using health economic models (cohort and individual patient level simulations), we will quantify the impact of varying donor referral decisions on healthcare costs, health benefits (quality-adjusted survival) and efficiency measures (time on waitlist and time to a kidney transplant).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e"},{"header":"2. Methods and analysis","content":"\u003cp\u003e \u003cb\u003e2.1 Consumer engagement\u003c/b\u003e: The MODUS study has been designed with input from peak consumer organisations and key stakeholders in delivery of Australia's organ donation and transplantation service. Our research partners have been integral to the development of this study protocol; the NSW Ministry of Health has underwritten the Biovigilance Public Health Register and will contribute to outcome development, and the NSW Organ and Tissue Donation Service will contribute expertise and help fidelity through close relationship with medical suitability advisors and transplanting hospitals; Kidney Health Australia has provided and ongoing vital consumer liaison. Increasing opportunities for transplantation is a priority for people with kidney disease. Our consumer liaisons will advise on project development, interpretation of results and dissemination strategies for research findings.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2.2 Study design and population\u003c/b\u003e: To profile donors, we will use an established dataset that contains outcome data for all candidates for deceased organ donors referred to NSW OTDS 2010\u0026ndash;2020, including those that proceeded to donation (actual donors), were deemed suitable for donation but never proceeded (intended donors) and were foregone for medical unsuitability (potential donors forgone)(Thomson et al. 2019). The data in our outcome models will be based on all people who entered the kidney waitlist for their first transplant between 1st July 2010 and 31st Dec 2019 in NSW from the Australian and New Zealand Dialysis and Transplantation Registry (ANZDATA) and OrganMatch. ANZDATA is a collaborative disease registry collecting clinical and treatment information on people undergoing dialysis or transplants for kidney failure from all treatment centres in Australia and New Zealand since 1977. OrganMatch is a clinical transplant system that facilitates compatibility matching of recipients and donors for organ transplantation and maintains the kidney transplant waiting list. We will exclude those who had multi-organ transplants (e.g., kidney\u0026thinsp;+\u0026thinsp;pancreas). Our study follow-up will be from waitlist entry until death, or 31st Dec 2019.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2.3 Outcomes measured\u003c/b\u003e: Aims 1 and 2 will measure outcomes in patients ever waitlisted for kidney transplantation, including time from waitlist entry to deceased donor transplant; clinical transitions after waitlist entry, such as removal from waitlist (i.e. temporary suspension and permanent) or death before transplant, number of deceased donor organ offers made and, probability of receiving a deceased donor transplant. Aim 3 will describe and categorise the reasons for medical unsuitability, donor quality, and potential donor numbers using current acceptance criteria. Aim 4 will measure the cost-effectiveness of increasing deceased donor acceptance using current guidelines, with health outcomes quantified using quality-adjusted life years (QALY) and costs measured in Australian dollars.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2.4 Analysis\u003c/b\u003e: Separate analyses will be conducted to meet each study's aim.\u003c/p\u003e \u003cp\u003e \u003cem\u003e2.4.1 Deceased donor profiling\u003c/em\u003e: We will investigate potential donors forgone who were deemed not medically suitable in NSW. Specifically, we will summarise demographic and clinical characteristics, including age, sex, blood group, comorbidities and calculated Australian kidney donor profile index (KDPI), of all consented potential donors and compare those declared medically unsuitable for donation with those that did proceed to donation. We will summarise the reasons given for why these potential donors did not proceed to donate, including where there were multiple reasons. Lastly, we will determine the proportion of potential donors forgone because of concerns around medical suitability, who were of better or the same quality as those who proceeded to donate, overall and by calendar year.\u003c/p\u003e \u003cp\u003e \u003cem\u003e2.4.2 Kidney waitlist dynamics\u003c/em\u003e: We will build a multi-state model of the kidney transplant waitlist and use this to describe kidney waitlist dynamics and evaluate all clinical transitions after entering the kidney waitlist. Clinical states will include active on the waitlist, temporary suspension, permanent removal, kidney transplant (deceased donor, living donor and paired kidney exchange donor), and death before transplant. We will exclude people who were already active on the waitlist (i.e., prevalent cases). Post-transplant clinical states will include graft failure, return to dialysis and re-entry to waitlist for subsequent transplant. We will use Markov models to evaluate patient factors associated with transitions after waitlist entry. Patient factors of interest include sex, age at waitlist entry, ethnicity, comorbidity burden and cause of kidney failure. Specifically, we will estimate transition intensity hazard ratios to indicate whether a transition is more or less likely to occur based on patient factors. Transitions of particular interest include from waitlist entry to suspension, suspension to waitlist (active), suspension to death before transplant, and waitlist entry to transplant.\u003c/p\u003e\u003cp\u003e \u003cem\u003e2.4.3 Describing the impact of donor decline for patients on the kidney waitlist\u003c/em\u003e: We will investigate patients who entered the kidney transplant waiting list in NSW from 2010\u0026ndash;2020. We will use records of ranked offers for every actual donor against potential recipients. Using records of which donor-recipient pairs were accepted, we will understand which donor-recipient pairs were offered but declined by transplant teams. We will estimate decline rates of the first donor-recipient paired offer by recipient characteristics, including blood group, sex, age, ethnicity, immunological sensitisation (PRA), and comorbidities. Subsequent outcomes after the decline of the first offer will be examined, including time to the next offer, time to the next better offer (measured as next donor offer with improved KDPI), number of offers to transplant if transplanted, rate and duration of time spent suspended from the list, receiving a transplant (deceased or living donor), and death. Time from decline to transplantation will be examined, by patient characteristics, using Kaplan-Meier curves and restricted mean survival time. We will use flexible parametric survival models to examine the time from decline to deceased donor transplantation for patients with different characteristics and to make adjusted predictions on time from decline to transplantation, evaluating impact of intersectional disadvantage for patients with different sociodemographic and clinical characteristics. Finally, we will assess whether the decline of the offer leads to the subsequent transplant of a better quality kidney; KDPIs of declined kidneys will be compared to accepted kidneys using the sign test for matched pairs.\u003c/p\u003e \u003cp\u003e \u003cem\u003e2.4.4 Economic Modelling of Increased Donor Acceptance\u003c/em\u003e: We will use cohort and individual-level simulation-based Markov models to compare the cost-effectiveness of the shift in clinical practice that encourages increased utilisation of potential donors with specific biovigilance concerns but who are within current guidelines (e.g., history of cancer or increased risk of infectious disease, including blood-borne virus) in the Australian healthcare setting. Biovigilance risk thresholds for acceptance of deceased organ donors will follow current clinical guidelines(The Transplantation Society of Australia and New Zealand 2019, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Health states included in our analysis include: being active on the transplant waitlist, being suspended from the waitlist, having a functioning kidney transplant, transplant failure and return to dialysis, death from kidney failure, and death from other causes, as well as health states specific to cancer or blood-borne viruses.\u003c/p\u003e\u003cp\u003eThe transition of kidney patients through different health states over a lifetime time horizon, will be simulated based on transition probabilities over 3-month time periods (Markov cycles). Health outcomes will be measured in terms of life-years gained and quality-adjusted life years (QALYs) gained, which incorporates both length and quality-of-life (scale 0\u0026ndash;1, where 0\u0026thinsp;=\u0026thinsp;death and 1\u0026thinsp;=\u0026thinsp;full health). Costs will be measured in Australian dollars using data obtained from the Medicare Benefits Schedule (MBS), Pharmaceutical Benefits Scheme (PBS), and relevant unit pricing based on Australian-Refined Diagnosis Related Group (AR-DRG) codes and the Independent Hospital Pricing Authority (IHPA) Net Efficient Price (NEP). A discount factor of 5% per year will be applied to costs and health outcomes, as per Australian government recommendations(Pharmaceutical Benefits Advisory Committee (PBAC) \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Medical Services Advisory Committee (MSAC) \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe cost-effectiveness of the shift in clinical practice to accept deceased donor organs with varying biovigilance risks, risk of cancer and blood-borne virus transmission aligned with current guidelines will be compared with the current practice, where these donors are typically declined. Cost-effectiveness will be measured as a ratio of incremental costs to incremental QALYs expressed as an incremental cost-effectiveness ratio (ICER) or net monetary benefit. A willingness to pay threshold will be determined based on estimates from the literature per QALY gained and used to interpret the ICER. A strategy will be interpreted as cost-effective if the ICER is less than the willingness to pay threshold per QALY gained. Sensitivity analyses will be conducted using varying willingness to pay thresholds.\u003c/p\u003e \u003cp\u003eWe will use individual-level simulation models to overcome some of the limitations of cohort-based Markov models, as well as to incorporate individual recipient and donor characteristics(Karnon and Haji Ali Afzali \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Briggs et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Recipient-level characteristics such as age, sex, blood group, number of previous kidney transplants, dialysis vintage, comorbidities, and donor characteristics such as age, sex, donor type (donation by brain or circulatory death), and Australian KDPI will be used. We plan to undertake a Distributional Cost-Effectiveness Analysis, a framework to incorporate health inequality impacts into the cost-effectiveness analysis comparing shifts in the clinical practice to accept deceased organ donors with increased risk of cancer and blood-borne virus transmission with current practice where these donors are typically declined(Cookson et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The model structure and analyses will follow best practice modelling guidelines from the International Society for Pharmacoeconomics and Outcomes Research(International Society for Pharmacoeconomics and Outcomes Research \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Comprehensive deterministic and probabilistic sensitivity analyses will be conducted to account for all parameter uncertainty in the models.\u003c/p\u003e \u003cp\u003eAnalyses will be performed using STATA, R and TreeAGE software.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2.5 Expected Outcomes\u003c/b\u003e: MODUS will provide evidence of the individual-level and health service effects of increasing acceptance of deceased donor kidneys that would otherwise be declined due to biovigilance concerns. Specifically, we expect to report our findings on 1) improvements in overall patient survival (life-years gained) and 2) quality of life (QALYs gained) by increasing the number of wait-listed people transplanted from donors with acceptable biovigilance risk who are currently foregone. We will also report on 3) any reductions in mortality while on the kidney waitlist, 4) any increases in disease transmission, and 5) the cost-effectiveness of a potential \u0026ldquo;informed biovigilance strategy\u0026rdquo; versus current practice.\u003c/p\u003e"},{"header":"3. Discussion","content":"\u003cp\u003eIncreasing the number of deceased organ donors available for transplantation is a global priority, but it is constrained by concerns of inadvertent transmission of cancer or infectious disease from deceased organ donors. Up to 60% of people referred for consideration for deceased organ donation in Australia do not proceed because of these concerns. However, we previously found opportunities to increase donation rates. In this work, we aim to describe how accepting or declining potential donors who did not proceed because of unfounded concerns around disease transmission will impact transplant recipients.\u003c/p\u003e \u003cp\u003eOur work will quantify the potential value of system change in terms of gains in survival and quality of life for people with kidney failure waiting for a transplant who would otherwise have remained waiting. In doing so, we will develop evidence to support policy and complex clinical decisions in Australia's organ donor referral process with potential global application. Our partner organisations will provide organisational structure and policy pathways to ensure sustainable knowledge transfer and implementation of MODUS findings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDissemination of findings:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results of MODUS - Modelling will be reported back to study CIs, AIs and all stakeholders including the NSW Ministry of Health, and consumers. Research findings will be presented at national and international professional network conferences and published in the scientific media. Publications will be led by study CIs, listed above, with acknowledgement of authorship to the relevant study members with expertise in the field, and consumes who significantly contributed to the development, analysis and translation of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBMR and KS contributed equally as the first authors of this manuscript. ACW and RLM were responsible for the conception and design of the MODUS Modelling study and the initiation of stakeholder collaborations. NDM, JB, and JH provided expertise in developing the described statistical analysis plans and data requirements. AR is a consumer co-author and has provided their perspective on idea generation and study conception. AR, PC, MW, KW and PK provided expertise on the manuscript, \u0026nbsp;study design and critical intellectual content. This work has been published on behalf of the MODUS Study Group: Professor Kirsten McCaffery, Dr Danielle Muscat, Prof Claire Vajdic, Dr Elena Cavazzoni, Prof Henry Pleass, Prof Nicholas Cross, Ms Rhonda Holdsworth, Prof Shilpanjali Jesudason and Prof William Rawlinson.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e:\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the University of Sydney Human Research Ethics Committee (Project No.: 2020/828).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConsent to participate and publish\u003c/strong\u003e:\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLinked patient health data was collated as a NSW Public Health Register under the Public Health Act, NSW 2010. Individual consent was waivered under the common public good. De-identified patient data was used for analysis. Participating institutions were all kidney dialysis and transplant centers in Australia and New Zealand that report to the Australian and New Zealand Dialysis and Transplant Registry (ANZDATA). No organs/tissues were obtained from prisoners in this study.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eData availability\u003c/strong\u003e:\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe data collated for this study is under the management of the NSW Ministry of Health as a Public Health Register. Summary-level data may be provided with appropriate permissions.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eFunding statement\u003c/strong\u003e:\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Australian National Health and Medical Research Council (NHMRC) Partnership Project grant (ID APP1171364). This support is in partnership with the NSW Ministry of Health, Office of the Chair, Kidney Health Australia and the NSW Organ and Tissue Donation Service.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u0026rsquo; \u003cstrong\u003estatement\u003c/strong\u003e:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe study investigators have no competing interests. All study members have declared all financial and nonfinancial affiliations to the HREC committee in the original ethics application.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements: \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data reported here have been supplied by the NSW Organ and Tissue Donation Service and the Australia and New Zealand Dialysis and Transplant Registry. The interpretation and reporting of these data are the responsibility of the authors and in no way should be seen as an official policy or interpretation of ANDATA or NSW OTDS. This work was funded by an Australian National Health and Medical Research Council Partnership Grant (#1171364). This support is in partnership with the NSW Ministry of Health, Office of the Chair, Kidney Health Australia and the NSW Organ and Tissue Donation Service.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eANZDATA Registry: Chapter 6: Australian Transplant Waiting List. In \u003cem\u003e43rd Report\u003c/em\u003e, edited by Australia and New Zealand Dialysis and Transplant Registry. Adelaide, Australia. (2020)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAustralian Organ and Tissue Donation and Transplantation Authority: Organ and Tissue Authority 2020\u0026ndash;21 Annual Report. In, edited by Australian Government Department of Health. (2021)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBriggs, A.D.M., Wolstenholme, J., Blakely, T., Peter, Scarborough: Choosing an epidemiological model structure for the economic evaluation of non-communicable disease public health interventions. Popul. Health Metrics. \u003cb\u003e14\u003c/b\u003e, 17 (2016)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChapman, J.R., Kanellis, J.: Kidney donation and transplantation in Australia: more than a supply and demand equation. Med. J. Aust. \u003cb\u003e209\u003c/b\u003e, 242\u0026ndash;243 (2018)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCollaborative Centre for Organ Donation Evidence: SAFEty and Biovigilance in Organ Donation (SAFEBOD) Technical Report. In. (2020)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCookson, R., Griffin, S., Norheim, O.F., Culyer, A.J., Chalkidou, K.: Distributional Cost-Effectiveness Analysis Comes of Age. Value Health. \u003cb\u003e24\u003c/b\u003e, 118\u0026ndash;120 (2021)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHedley, J.A., Kelly, P.J., Waller, K.M.J., Thomson, I.K., De La Mata, N.L., Rosales, B.M., Wyburn, K., Webster, A.C.: Perceived Versus Verified Cancer History and Missed Opportunities for Donation in an Australian Cohort of Potential Deceased Solid Organ Donors. Transplantation direct. \u003cb\u003e8\u003c/b\u003e, e1252 (2022)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInternational Society for Pharmacoeconomics and Outcomes Research: Good Practices for Outcomes Research. In. (2018)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKarnon, J., Haji Ali Afzali, H.: 'When to use discrete event simulation (DES) for the economic evaluation of health technologies? A review and critique of the costs and benefits of DES', \u003cem\u003ePharmacoeconomics\u003c/em\u003e, 32: 547\u0026thinsp;\u0026ndash;\u0026thinsp;58. (2014)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhanal, N., Lawton, P.D., Cass, A., McDonald, S.P.: Disparity of access to kidney transplantation by Indigenous and non-Indigenous Australians. Med. J. Aust. \u003cb\u003e209\u003c/b\u003e, 261\u0026ndash;266 (2018)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiyanage, T., Ninomiya, T., Jha, V., Neal, B., Patrice, H.M., Okpechi, I., Zhao, M.H., Lv, J., Garg, A.X., Knight, J., Rodgers, A., Gallagher, M., Kotwal, S., Cass, A., Perkovic, V.: Worldwide access to treatment for end-stage kidney disease: a systematic review. Lancet. \u003cb\u003e385\u003c/b\u003e, 1975\u0026ndash;1982 (2015)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLysaght, M.J.: Maintenance dialysis population dynamics: current trends and long-term implications. J. Am. Soc. Nephrol. \u003cb\u003e13\u003c/b\u003e(Suppl 1), S37\u0026ndash;40 (2002)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMedical Services Advisory Committee (MSAC): Guidelines for preparing assessments for the Medical Services Advisory Committee. In, edited by Department of Health. Canberra, Australia: Medical Services Advisory Committee (MSAC),. (2021)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePharmaceutical Benefits Advisory Committee (PBAC): Guidelines for preparing submissions to the Pharmaceutical Benefits Advisory Committee (PBAC). In, edited by Department of Health. Canberra, Australia: Pharmaceuitcal Benefits Advisory Committee (PBAC),. (2016)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSypek, M.P., Clayton, P.A., Lim, W., Hughes, P., Kanellis, J., Wright, J., Chapman, J., McDonald, S.P.: 'Access to waitlisting for deceased donor kidney transplantation in Australia', \u003cem\u003eNephrology (Carlton)\u003c/em\u003e, 24: 758\u0026thinsp;\u0026ndash;\u0026thinsp;66. (2019)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTalamantes, E., Norris, K.C., Mangione, C.M., Moreno, G., Waterman, A.D., Peipert, J.D., Bunnapradist, S., Huang, E.: Linguistic Isolation and Access to the Active Kidney Transplant Waiting List in the United States. Clin. J. Am. Soc. Nephrol. \u003cb\u003e12\u003c/b\u003e, 483\u0026ndash;492 (2017)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThe Transplantation Society of Australia and New Zealand: Clinical guidelines for organ transplantation from deceased donors. In, edited by Australian Organ and Tissue Authority. Canberra, Australia: The Transplantation Society of Australia and New Zealand. (2023)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThomson, I.K., Rosales, B.M., Kelly, P.J., Wyburn, K., Waller, K.M.J., Hirsch, D., O'Leary, M.J.: and A. C. Webster. 2019. 'Epidemiology and Comorbidity Burden of Organ Donor Referrals in Australia: Cohort Study 2010\u0026ndash;2015'. Transplantation direct, \u003cb\u003e5\u003c/b\u003e: e504\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWaller, K.M.J., De La Mata, N.L., Rosales, B.M., Hedley, J.A., Kelly, P.J., Thomson, I.K., O'Leary, M.J., Cavazzoni, E., Ramachandran, V., Rawlinson, W.D., Wyburn, K.R., Webster, A.C.: 'Characteristics and Donation Outcomes of Potential Organ Donors Perceived to be at Increased Risk for Blood Borne Virus Transmission: an Australian Cohort Study 2010\u0026ndash;2018', \u003cem\u003eTransplantation\u003c/em\u003e. (2021)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWaller, K.M.J., Wyburn, K.R., Shackel, N.A., O'Leary, M.J., Kelly, P.J., Webster, A.C.: 'Hepatitis Transmission Risk in Kidney Transplantation (the HINT study): A Cross-Sectional Survey of Transplant Clinicians in Australia and New Zealand', \u003cem\u003eTransplantation\u003c/em\u003e, 102: 146\u0026thinsp;\u0026ndash;\u0026thinsp;53. (2018)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWebster, A.C., Nagler, E.V., Morton, R.L., Masson, P.: Lancet. \u003cb\u003e389\u003c/b\u003e, 1238\u0026ndash;1252 (2017). 'Chronic Kidney Disease'\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWyld, M.L.R., Wyburn, K.R., Chadban, S.J.: 'Global Perspective on Kidney Transplantation: Australia', \u003cem\u003eKidney360\u003c/em\u003e, 2: 1641-44. (2021)\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Kidney Failure, Transplant Waitlist, Organ Allocation, Biovigilance, Population-based study, Health Economic Evaluation","lastPublishedDoi":"10.21203/rs.3.rs-4628090/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4628090/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIncreasing deceased organ donation is a global priority constrained by concerns of inadvertent transmission of cancer or infectious disease from deceased organ donors. Up to 60% of potential donors referred for consideration for deceased organ donation in Australia do not proceed for biovigilance concerns. However, there are opportunities to increase acceptance. We aim to describe the impact of accepting or declining potential donors forgone for biovigilance concerns on patient and transplant outcomes. We will use data for all potential donors referred for consideration for deceased organ donation and data for patients ever waitlisted for kidney transplantation in New South Wales, Australia\u0026rsquo;s most populous state, 2010\u0026ndash;2020. We will 1) describe the patient journey on the kidney transplant waitlist, including episodes of suspension and reactivation, time waiting and whether transplanted; 2) describe the characteristics of patients on the kidney transplant waitlist who decline a deceased donor organ offer and patient outcomes after their first decline; 3) determine potential gains made through increased donor acceptance and profile potential donors forgone for medical suitability; 4) use economic modelling to investigate the benefits and costs of increasing donor acceptance. Research findings will be presented at scientific conferences, published in the scientific media, and via collaborator networks.\u003c/p\u003e","manuscriptTitle":"Maximising Organ Donor Utility System-wide (MODUS): A study protocol for using linked health services data in multi-modal modelling of kidney transplant waitlist outcomes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-18 15:40:10","doi":"10.21203/rs.3.rs-4628090/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dbe38b3d-268b-4b53-9bb5-a026019eee03","owner":[],"postedDate":"July 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-07-18T15:40:10+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-18 15:40:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4628090","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4628090","identity":"rs-4628090","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}