Variables of importance in the Scientific Registry of Transplant Recipients database predictive of heart transplant waitlist mortality

Abstract

The prelisting variables essential for creating an accurate heart transplant allocation score based on survival are unknown. To identify these we studied mortality of adults on the active heart transplant waiting list in the Scientific Registry of Transplant Recipients database from January 1, 2004 to August 31, 2015. There were 33 069 candidates awaiting heart transplantation: 7681 UNOS Status 1A, 13 027 Status 1B, and 12 361 Status 2. During a median waitlist follow-up of 4.3 months, 5514 candidates died. Variables of importance for waitlist mortality were identified by machine learning using Random Survival Forests. Strong correlates predicting survival were estimated glomerular filtration rate (eGFR), serum albumin, extracorporeal membrane oxygenation, ventricular assist device, mechanical ventilation, peak oxygen capacity, hemodynamics, inotrope support, and type of heart disease with less predictive variables including antiarrhythmic agents, history of stroke, vascular disease, prior malignancy, and prior tobacco use. Complex interactions were identified such as an additive risk in mortality based on renal function and serum albumin, and sex-differences in mortality when eGFR >40 mL/min/1.73 m. Most predictive variables for waitlist mortality are in the current tiered allocation system except for eGFR and serum albumin which have an additive risk and complex interactions.

Keywords: Scientific Registry for Transplant Recipients (SRTR); artificial organs/support devices: heart/ventricular assist devices; clinical research/practice; gender; health services and outcomes research; heart transplantation/cardiology; organ procurement and allocation; organ transplantation in general; patient survival; waitlist management.

Figure 1:. Sex-differences in Heart Transplant Waitlist Survival Based on Estimate Glomerular Filtration Rate and UNOS Status at Time of Listing

Risk-adjusted relationship of 1, 2, 3, and 5 year survival (OOB=out-of-bag survival) on the transplant waitlist and estimated glomerular filtration rate (eGFR) at listing for UNOS Status 1A, 1B, and 2 candidates. The shape of all curves is estimated non-parametrically without model assumptions. Note that there is near linear decrease in survival as eGFR falls below 80 mL/min/1.73 m², but for eGFR greater than this, there is no relationship of survival to eGFR. This holds for all UNOS Statuses. Although eGFR adjusts creatinine levels for age, sex, and race, there remains a notable small interaction of the relation on survival to eGFR with respect to sex, which is also depicted on these curves.

Figure 2:. Heart Transplant Waitlist Survival Based on Serum Albumin and UNOS Status at Time of Listing

Risk-adjusted relationship of 1, 2, 3 and 5 year survival (OOB=out-of-bag survival) on the heart transplant waiting list and serum album at listing for UNOS Status 1A, 1B, and 2 candidates. The shape of all curves is estimated non-parametrically without model assumptions. Note the near linear decrease in survival with progressively lower albumin levels.

Figure 3:. Heart Transplant Waitlist Survival Based on Serum Albumin, Estimated Glomerular Filtration Rate, and UNOS Status at Time of Listing

Three dimensional plots using random survival forest analysis were constructed to depict the association between serum albumin, estimated glomerular filtration rate (eGFR) and UNOS Status at time of listing. 1 year survival is compared to 5 year survival for UNOS Status 1A, 1B, and 2 candidates.

Figure 4:. Variables of Importance Predicting Heart Transplant Waitlist Mortality

Random Survival Forest investigation of variables predicting heart transplant waitlist mortality based on initially listing candidates as UNOS Status 1A, 1B or 2. Boxes encompass median (line) and 25th and 75th percentile confidence limits, and whiskers 95% confidence limits. A value of 1.5% as reported for estimated glomerular filtration rate (eGFR) among UNOS Status 1A candidates means that without eGFR in the survival model we would misclassify 1.5% of new candidates. Thus, given two new candidates we would incorrectly identify which has worse survival on average 1.5% of the time.

Figure 5:. Heart Transplant Waitlist Survival Based on Blood Type and Body Mass Index

Risk-adjusted 3 year survival (OOB=out-of-bag survival) on the heart transplant waiting list based on blood type (A, B, AB, O) and body mass index for UNOS Status 1A candidates. The shape of all curves is estimated non-parametrically without model assumptions.