Correcting the Sex Disparity in MELD-na

Nicholas L. Wood; Douglas VanDerwerken; Dorry L. Segev; Sommer E. Gentry


American Journal of Transplantation. 2021;21(10):3296-3304. 

In This Article

Abstract and Introduction


MELD-Na appears to disadvantage women awaiting liver transplant by underestimating their mortality rate. Fixing this problem involves: (1) estimating the magnitude of this disadvantage separately for each MELD-Na, (2) designing a correction for each MELD-Na, and (3) evaluating corrections to MELD-Na using simulated allocation. Using Kaplan-Meier modeling, we calculated 90-day without-transplant survival for men and women, separately at each MELD-Na. For most scores between 15 and 35, without-transplant survival was higher for men by 0–5 percentage points. We tested two proposed corrections to MELD-Na (MELD-Na-MDRD and MELD-GRAIL-Na), and one correction we developed (MELD-Na-Shift) to target the differences we quantified in survival across the MELD-Na spectrum. In terms of without-transplant survival, MELD-Na-MDRD overcorrected sex differences while MELD-GRAIL-Na and MELD-Na-Shift eliminated them. Estimating the impact of implementing these corrections with the liver simulated allocation model, we found that MELD-Na-Shift alone eliminated sex disparity in transplant rates (p = 0.4044) and mortality rates (p = 0.7070); transplant rates and mortality rates were overcorrected by MELD-Na-MDRD (p = 0.0025, p = 0.0006) and MELD-GRAIL-Na (p = 0.0079, p = 0.0005). We designed a corrected MELD-Na that eliminates sex disparities in without-transplant survival, but allocation changes directing smaller livers to shorter candidates may also be needed to equalize women's access to liver transplant.


Women are more likely than men to die on the liver transplant waitlist, more likely to be removed from the waitlist for being "too sick" for transplant, and less likely to receive a transplant.[1–6] Some of these sex differences might stem from lower serum creatinine (and hence a lower model for end-stage liver disease [MELD-Na] score) for women versus men with similar renal dysfunction.[1,3,5,7–12] However, the contribution of creatinine to MELD-Na varies across the score spectrum because creatinine measurements are rounded up to 1.0 and capped at 4.0 mg/dl,[13] so it is likely that sex differences also vary across the MELD-Na score spectrum. While both Myers et al. and Locke et al.[5,14] have estimated the average difference (across all MELD-Na scores) between men and women in without-transplant survival, correcting MELD-Na scores to resolve sex disparities requires estimating these differences separately for each MELD-Na score.

There have been recent calls to develop and study policy changes to mitigate sex disparities in liver transplantation.[15,16] An early approach was to correct serum creatinine based on the modification of diet in renal disease (MDRD) formula for estimated GFR (eGFR).[7] This resulted in 65% of women having an increase of 2 or 3 points under the MDRD correction, but unfortunately this correction to MELD was no better than MELD at predicting 3-, 6-, 9-, or 12-month mortality for women,[10] with similar results in subsequent studies of this approach.[5,17,18] Asrani et al. refit MELD-Na to include eGFR via the glomerular filtration rate in liver disease (GRAIL) formula. They found that MELD-GRAIL-Na was better than MELD-Na at predicting waitlist mortality for women,[19,20] but only tested this on average (vs. for each MELD-Na score), and did not test this in real-world simulations of allocation. A systems engineering approach might be to separately shift each woman's MELD-Na according to observed sex differences in survival at that MELD-Na, effectively "reverse engineering" the disparities so that men and women with similar without-transplant survival will have the same score; we will present such an approach called MELD-Na-Shift.

Regardless of whether a corrected MELD-Na score yields an unbiased estimate of without-transplant survival for men and women, the ultimate goal is to remedy all disadvantages women have faced awaiting transplant. Only a real-world, clinically detailed simulated allocation model that includes disease etiology, donor and candidate size, accept/decline decisions, and uncertainty in disease progression and organ availability can answer the question of whether a corrected score would additionally mitigate sex disparity in transplant and mortality rates. None of the previously proposed corrections have been tested in a simulated allocation model. Unfortunately, the liver simulated allocation model (LSAM) underestimates the magnitude of the sex disparity in transplant rates and does not explicitly model decreased acceptance of larger livers for candidates of shorter stature, which limits the use of this tool to address height and size mismatch as a driver of sex disparity in transplantation. We therefore limit our main inferences to whether we can correct the sex bias in estimated without-transplant survival.

To explore ways to fix the sex disparity in MELD-Na, we quantified sex differences in without-transplant survival, independent of allocation and separately at each MELD-Na score, using Kaplan-Meier modeling in contrast to standard Cox regression. We then re-calculated without-transplant survival for women using two previously proposed corrections to MELD-Na (MELD-Na-MDRD and MELD-GRAIL-Na), and one correction of our own design that shifts each MELD-Na score for women to the MELD-Na of men with similar without-transplant survival (MELD-Na-Shift). Finally, we applied these MELD-Na corrections in a simulated allocation model to determine whether sex disparities in transplant and mortality rates could be reduced.