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


In this national study of the liver transplant waitlist, we found that women had lower 90-day without-transplant survival compared to men at most MELD-Na scores between 15 and 35, but not at the highest MELD-Na scores. The difference, although statistically significant, was small, varying from about 0 to 5 percentage points depending on MELD-Na. We investigated two proposed MELD-Na corrections (MELD-Na-MDRD and MELD-GRAIL-Na) and one correction of our own design that shifted female MELD-Na to the corresponding male MELD-Na that equalized 90-day without-transplant survival (MELD-Na-Shift). MELD-Na-MDRD overcorrected the differences in without-transplant survival, whereas MELD-GRAIL-Na and MELD-Na-Shift eliminated the differences. We tested these MELD-Na corrections in a simulated allocation model to determine their effect on men and women in the presence of transplant. In simulation, MELD-Na-MDRD and MELD-GRAIL-Na overcorrected the differences in transplant and mortality rates between men and women, whereas MELD-Na-Shift eliminated the differences in transplant and mortality rates.

Our decision to censor transplants in a Kaplan-Meier framework was deliberate and distinguishes our analysis from others on this topic that use competing risk methodology. Kaplan-Meier analysis estimates survival in the absence of transplant while competing risk analysis estimates survival in the presence of transplant. For an excellent elaboration on the appropriate uses as well as the drawbacks of each method, see the discussion in Kim et al.[24] Accordingly, our research answers the question of whether women's without-transplant survival is systematically overestimated by the MELD-Na score. We do not address the question of whether women receive fewer transplants because their smaller size forces them to decline more livers.

Our methodology is novel because we separately estimated the sex disparity in without-transplant survival for each MELD-Na score, allowing us to reverse engineer a novel MELD-Na-Shift correction which targets specific MELD-Na scores where there is a disparity, and because our methodology is fully non-parametric and uses data from every new MELD-Na update rather than only at listing. Although it may seem more intuitive to increase the MELD-Na score of all female candidates equally regardless of score, doing so would overcorrect the disparity in without-transplant survival even with an increase in only one point (see Supporting Document). Additionally, we used inverse probability censoring weights to overcome one of the major drawbacks mentioned by Kim et al., namely the questionable assumption of noninformative censoring (see the Appendix for more details).

Our findings are consistent with those of others who also censor for transplant, such as Myers et al. and Locke et al.[5,14] Myers et al. showed that a Cox model with various baseline variables and MELD had a hazard ratio for female sex of 1.07 (indicating moderate bias in favor of males), whereas a similar model with INR, bilirubin, and eGFR instead of serum creatinine had a hazard ratio for female sex of 0.85 (indicating overcorrection). Locke et al. showed that accounting for MELD-Na by weighting a Cox model increased the sex disparity in waitlist survival (the hazard ratio changed from a baseline of 1.09 to 1.14) and slightly decreased the sex disparity in the probability of receiving a transplant (hazard ratio changed from 0.86 to 0.87).

Other researchers including Lai et al. and Allen et al. have used a competing risk framework, which estimates waitlist mortality in the presence of transplant, combining liver disease risk with the effects of allocation.[1,25] Lai et al. found that much of the disparity between men and women in mortality can be explained by differences in height. Allen et al. used Cox modeling with competing risks to find that differences in height and exception scores accounted for most of the disparity between men and women in transplant rates. Their Cox model suggested that giving women 1 or 2 additional MELD-Na points would substantially increase the number of women who would receive liver transplants. They called for further exploration using sophisticated simulation software, a call we have answered. Using LSAM, we found that each of our proposed corrections to MELD-Na resulted in a significant increase in the number of transplants for women over our 3-year simulation: 155 for MELD-Na-Shift, 318 for MELD-GRAIL-Na, and 404 for MELD-Na-MDRD.

Bowring et al. showed that offered livers tend to be too large for female candidates to accept, which might explain the differences in transplant rates.[26] Darden et al. showed that differences in size account for 19% of the disparity in transplant rates between men and women.[27] Our simulation results agree that men are transplanted at a higher rate than women and that women die on the waitlist at a higher rate than men. However, LSAM underestimated the magnitude of these differences. Using LSAM to model share 35 (the allocation system in effect during our simulation period), we estimated that women were transplanted at 90.57% of the rate of men and died on the waitlist at 103% of the rate of men, whereas in reality women were transplanted at around 83% of the rate of men and died on the waitlist at around 105% of the rate of men.[6] As a result, it is not entirely clear whether MELD-Na-MDRD and MELD-GRAIL-Na would truly be over-corrections to transplant and mortality rates. For this reason, additional policy changes aimed at the sex disparity in transplant rates (such as donor-candidate size matching) may be warranted.

We hypothesize two reasons that LSAM might underestimate the gender gap in transplant and mortality rates. First, LSAM's accept/decline models do take sex into account (such that men are slightly more likely to accept an offer than women), but the models do not incorporate candidate height. This may partially explain why LSAM underestimated male transplant rate and overestimated female transplant rate. Second, LSAM's candidate generator imputes disease trajectories for candidates who were transplanted in real life. The candidate generator does this by matching status updates via a linear predictor for candidate mortality. This mortality predictor, however, does not account for candidate sex. The imputed disease trajectories for women might actually be disease trajectories from male candidates, and thus may underestimate women's true risk of mortality.

We purposefully did not account for disease etiology when estimating without-transplant survival, as MELD-Na is identically defined for all etiologies. However, we found that certain disease etiologies are more prevalent in men than in women (and vice versa). Looking at without-transplant survival for candidates with NASH, and for candidates with hepatitis C, men still had higher without-transplant survival than women for most MELD-Na scores. For candidates with alcoholic cirrhosis, men did not consistently have higher without-transplant survival compared to women, nor vice versa. This suggests that the difference in without-transplant survival between men and women is not due to differences in disease etiology, however, small sample sizes make it difficult to draw conclusions from these analyses (see Supporting Document).

We found that women are disadvantaged on the liver waitlist as evidenced by lower without-transplant survival when compared to men at most MELD-Na scores between 15 and 35, and by lower transplant rates and higher mortality rates. Both MELD-GRAIL-Na and our MELD-Na-Shift corrections eliminated the sex disparity in without-transplant survival. Only our MELD-Na-Shift correction eliminated the sex disparity in transplant rates and mortality rates in simulated allocation modeling, however, limitations in LSAM's ability to capture the magnitude of this disparity leave open MELD-GRAIL-Na as another possibly effective correction. Allocating livers via MELD-Na-Shift or MELD-GRAIL-Na could reduce the disadvantage women face awaiting transplant due to the use of serum creatinine in MELD-Na, however, additional allocation changes may be needed to address the issue of size mismatch for women and candidates of shorter stature.[28]