Expected number of deaths in the liver transplantation waiting list in the state of São Paulo, Brazil

THE OPTIMUM LEVEL OF MELD TO MINIMIZE THE MORTALITY ON LIVER TRANSPLANTATION WAITING LIST, AND LIVER TRANSPLANTED PATIENT IN SÃO PAULO STATE, BRAZIL

BACKGROUND

After validation in multiple types of liver disease patients, the MELD score was adopted as a standard by which liver transplant candidates with end-stage liver disease were prioritized for organ allocation in the United States since 2002, and in Brazil, since 2006.

AIMS

To analyze the mortality profile of patients on the liver transplant waiting list correlated to MELD score at the moment of transplantation.

METHODS

This study used the data from the Secretary of Health of the São Paulo State, Brazil, which listed 22,522 patients, from 2006 (when MELD score was introduced in Brazil) until June 2009. Patients with acute hepatic failure and tumors were included as well. We also considered the mortality of both non-transplanted and transplanted patients as a function of the MELD score at presentation.

RESULTS

Our model showed that the best MELD score for patients on the liver transplant waiting list associated to better results after liver transplantation was 26.

CONCLUSIONS

We found that the best score for applying to liver transplant waiting list in the State of São Paulo was 26. This is the score that minimizes the mortality in both non-transplanted and liver transplanted patients.

A mathematical model for optimizing the indications of liver transplantation in patients with hepatocellular carcinoma

BACKGROUND

The criteria for organ sharing has developed a system that prioritizes liver transplantation (LT) for patients with hepatocellular carcinoma (HCC) who have the highest risk of wait-list mortality. In some countries this model allows patients only within the Milan Criteria (MC, defined by the presence of a single nodule up to 5 cm, up to three nodules none larger than 3 cm, with no evidence of extrahepatic spread or macrovascular invasion) to be evaluated for liver transplantation. This police implies that some patients with HCC slightly more advanced than those allowed by the current strict selection criteria will be excluded, even though LT for these patients might be associated with acceptable long-term outcomes.

METHODS

We propose a mathematical approach to study the consequences of relaxing the MC for patients with HCC that do not comply with the current rules for inclusion in the transplantation candidate list. We consider overall 5-years survival rates compatible with the ones reported in the literature. We calculate the best strategy that would minimize the total mortality of the affected population, that is, the total number of people in both groups of HCC patients that die after 5 years of the implementation of the strategy, either by post-transplantation death or by death due to the basic HCC. We illustrate the above analysis with a simulation of a theoretical population of 1,500 HCC patients with tumor size exponentially. The parameter λ obtained from the literature was equal to 0.3. As the total number of patients in these real samples was 327 patients, this implied in an average size of 3.3 cm and a 95% confidence interval of [2.9; 3.7]. The total number of available livers to be grafted was assumed to be 500.

RESULTS

With 1500 patients in the waiting list and 500 grafts available we simulated the total number of deaths in both transplanted and non-transplanted HCC patients after 5 years as a function of the tumor size of transplanted patients. The total number of deaths drops down monotonically with tumor size, reaching a minimum at size equals to 7 cm, increasing from thereafter. With tumor size equals to 10 cm the total mortality is equal to the 5 cm threshold of the Milan criteria.

CONCLUSION

We concluded that it is possible to include patients with tumor size up to 10 cm without increasing the total mortality of this population.

Does anti-hepatitis B virus vaccine make any difference in long-term number of liver transplantation?

BACKGROUND

Hepatitis B virus (HBV) infection is a major cause of morbidity and mortality worldwide. Chronic hepatitis B infection is associated with an increased risk of cirrhosis, hepatic decompensation, and hepatocellular carcinoma. Our aim is to analyze, through a mathematical model, the potential impact of anti-HBV vaccine in the long-term (that is, decades after vaccination) number of LT.

METHODS

The model simulated that the prevalence of HBV infection was 0.5% and that approximately 20% of all the liver transplantation carried out in the state of São Paulo are due to HBV infection.

RESULTS

The theoretical model suggests that a vaccination program that would cover 80% of the target population would reach a maximum of about 14% reduction in the LT program.

CONCLUSION

Increasing the vaccination coverage against HBV in the state of São Paulo would have a relatively low impact on the number of liver transplantation. In addition, this impact would take several decades to materialize due to the long incubation period of liver failure due to HBV.

A mathematical model for shortening waiting time in pancreas-kidney transplantation

AIM: To simulate a hypothetical increase of 50% in the number of pancreas-kidney (PK) transplantations using less-than-ideal donors by a mathematical model.

METHODS: We projected the size of the waiting list by taking into account the incidence of new patients per year, the number of PK transplantations carried out in the year and the number of patients who died on the waiting list or were removed from the list for other reasons. These variables were treated using a model developed elsewhere.

RESULTS: We found that the waiting list demand will meet the number of PK transplantation by the year 2022.

CONCLUSION: In future years, it is perfectly possible to minimize the waiting list time for pancreas transplantation through expansion of the donor pool using less-than-ideal donors.

Increasing liver transplantation waiting list mortality: a report from the Australian National Liver Transplantation Unit, Sydney

BACKGROUND

We aimed to describe the demand for liver transplantation (LTx) and patient outcomes on the waiting list at the Australian National Liver Transplantation Unit, Sydney over the last 20 years.

METHODS

We performed a retrospective analysis with the data divided into three eras: 1985-1993, 1994-2000 and 2001-2008.

RESULTS

The number of patients accepted for LTx increased from 320 to 372 and 548 (P < 0.001) with the number of LTx being performed increasing from 262 to 312 and 452 respectively (P < 0.001). The median adult recipient age increased from 45 to 48 and 52 years (P < 0.001) while it decreased in children from 4 to 2 and 1 years respectively (P = 0.001). In parallel, the deceased donor offers decreased from 1003 to 720 and 717 (P < 0.001). Methods to improve access to donor livers have been used with the use of split livers, extended criteria and non-heart beating donors, resulting in increased acceptance of deceased donor offers by 65% and 115% in the second and third eras when compared with the first era (P < 0.001). However, the adult median waiting time has increased from 23 to 41 and 120 days respectively (P < 0.001). This was associated with increased adult mortality on the waiting list from 23 to 40 and 122 respectively (P < 0.001).

CONCLUSIONS

Despite the increasing proportion of donor offers being used, the waiting list mortality is increasing. A solution to this problem is an increase in organ donation to keep pace with the escalating demand for LTx.

Potential effect of using ABO-compatible living-donor liver transplantation

Liver transplantation increased 1.84-fold from 1988 to 2004. However, the number of patients on the waiting list for a liver increased 2.71-fold, from 553 to 1500. We used a mathematical equation to analyze the potential effect of using ABO-compatible living-donor liver transplantation (LDLT) on both our liver transplantation program and the waiting list. We calculated the prevalence distribution of blood groups (O, A, B, and AB) in the population and the probability of having a compatible parent or sibling for LDLT. The incidence of ABO compatibility in the overall population was as follows: A, 0.31; B, 0.133; O, 0.512; and AB, 0.04. The ABO compatibility for parent donors was blood group A, 0.174; B, 0.06; O, 0.152; and AB, 0.03; and for sibling donors was A, 0.121; B, 0.05; O, 0.354; and AB, 0.03. Use of LDLT can reduce the pressure on our liver transplantation waiting list by decreasing its size by at least 16.5% at 20 years after its introduction. Such a program could save an estimated 3600 lives over the same period.

The potential impact of using donations after cardiac death on the liver transplantation program and waiting list in the state of Sao Paulo, Brazil

Liver transplantation was first performed at the University of Sao Paulo School of Medicine in 1968. Since then, the patient waiting list for liver transplantation has increased at a rate of 150 new cases per month. Liver transplantation itself rose 1.84-fold (from 160 to 295) from 1988 to 2004. However, the number of patients on the liver waiting list jumped 2.71-fold (from 553 to 1500). Consequently, the number of deaths on the liver waiting list moved to a higher level, from 321 to 671, increasing 2.09-fold. We have applied a mathematical model to analyze the potential impact of using a donation after cardiac death (DCD) policy on our liver transplantation program and on the waiting list. Five thousand one hundred people died because of accidents and other violent causes in our state in 2004; of these, only 295 were donors of liver grafts that were transplanted. The model assumed that 5% of these grafts would have been DCD. We found a relative reduction of 27% in the size of the liver transplantation waiting list if DCD had been used by assuming that 248 additional liver transplants would have been performed annually. In conclusion, the use of DCD in our transplantation program would reduce the pressure on our liver transplantation waiting list, reducing it by at least 27%. On the basis of this model, the projected number of averted deaths is about 41,487 in the next 20 years.