While conducting research on the links between lung function and cell-transplantation risks, Dr. Jason Chien and colleagues in the Clinical Research Division realized they could create an easy-to-use tool to estimate a patient's risk of mortality — with the goal that doctor with routine clinical information collected before cell transplantation could use the tool.
Basing their tool on medical records of more than 2,800 patients from the Center and the Seattle Cancer Care Alliance, the researchers identified eight variables that could help estimate — before the transplant occurred — the risk of mortality within two years after cell transplantation. The result, which the researchers call the Pretransplant Assessment of Mortality (PAM) score, was found to be quite a reliable estimate of mortality. Although previous research independently assessed the association between the multiple clinical factors in this study and mortality risk, Chien's new study integrates numerous variables into one predictive tool.
The results were published in the March 21 issue of the journal Annals of Internal Medicine.
Accurate estimates of a patient's risk of death due to transplant-related complications may ultimately aid doctors and patients considering whether cell transplantation is the best course of action.
The researchers have developed an online PAM-score calculator. The online tool is aimed primarily at clinicians caring for cell-transplant patients and secondarily at clinical researchers designing or assessing clinical trials.
Chien said that the calculation is possible once the physician has collected data including the patient's age, disease severity, transplant regimen, kidney function, liver and lung function, and donor type before a cell-transplantation procedure.
"We're trying to reach other oncologists nationally and internationally so they can use this tool," Chien said. "For instance, if a patient walks into a small transplant institute in the Midwest, all they have to do is obtain these eight variables and they'll be able to predict what their risk for death is during the first two years after transplant. The clinician can go to the Web site, make the calculations and come up with the risk themselves."
"With the PAM score, a community oncologist or primary-care physician can give patients accurate information about their chances of survival after a transplant," said Dr. Paul Martin, a co-author of the study from the Clinical Research Division. "This type of information really helps in making decisions about treatment."
Chien, a lung specialist, has dedicated his career at the Center to understanding how changes in lung function affect cell-transplant patients. Although he previously discovered a strong relationship between lung function and the risk for death (See www.fhcrc.org/about/pubs/center_news/2005/dec15/sart4.xml), Chien knew that this information must be interpreted in the context of all the other clinical problems that patients may have. The challenge was how to facilitate the assessment of this risk. "Our goal was to develop a user-friendly tool for predicting a patient's death risk before they actually get the transplant — a universal tool that can be easily used by all clinicians," Chien said.
In addition to Martin, Chien's co-authors on the paper included Dr. David Au, from Veterans Affairs Puget Sound Health Care System, Health Services Research and Development; and Dr. Tanyalak Parimon, who analyzed data while working at the Center as a pulmonary research fellow.
Despite advances in recent years, mortality after transplantation remains high. Risk for death after cell transplantation depends on factors such as the underlying disease, stage of the disease, type of donor, level of exposure to total-body radiation, certain methods of radiation delivery, and heart, lung or kidney dysfunction.
To develop the PAM algorithm, Chien and colleagues randomly divided 12 years of patient data into two groups. The data for the first group of patients served to develop the model; the data for the second group, which was subdivided into various subgroups depending upon the year of transplant and type of disease, served to validate the model. The clinical data used to create the calculation tool were collected from transplants performed between 1990 and 2002 at the Center and SCCA.
Weighing the risks
The researchers acknowledged that the performance of the tool needs to be validated using data from other transplant centers. "The most important aspect of any prediction tool is how well it performs across different populations. Although the Hutchinson Center's mortality rates are similar to others internationally, different transplant centers may have differences in the types of patients they treat and how they treat their patients," Chien said. "This is why we encourage the international community of transplant oncologists to consider applying the PAM score to their patients and determine if this tool will be clinically useful for everyone."
While the study awaits validation in other populations and settings, Chien is confident that the system provides a powerful predictive tool that is grounded in extensive data. "We studied more diverse patients over a longer period than anyone has ever done before," he said. "I believe this study will likely have a significant impact on how patients are selected for bone-marrow transplants."
The researchers acknowledged that decisions regarding risks of proceeding with a transplant are sensitive. However, Chien said that if presented with realistic risk assessments and the option of living without the complications and toxicity of transplantation, some patients might opt out of the procedure, while others may embrace the opportunity for a cure.
"If you can tell someone that they have a very high chance of death, would they actually go through a transplant or should they go through a transplant? It becomes a quality-of-life issue," he said. "Hopefully we'll be able to provide them with information that they can use to help make a more informed decision."