Clinical factors and the decision to transfuse chronic dialysis patients.
OBJECTIVE
Red blood cell transfusion was previously the principle therapy for anemia in CKD but became less prevalent after the introduction of erythropoiesis-stimulating agents. This study used adaptive choice-based conjoint analysis to identify preferences and predictors of transfusion decision-making in CKD.


METHODS
A computerized adaptive choice-based conjoint survey was administered between June and August of 2012 to nephrologists, internists, and hospitalists listed in the American Medical Association Masterfile. The survey quantified the relative importance of 10 patient attributes, including hemoglobin levels, age, occult blood in stool, severity of illness, eligibility for transplant, iron indices, erythropoiesis-stimulating agents, cardiovascular disease, and functional status. Triggers of transfusions in common dialysis scenarios were studied, and based on adaptive choice-based conjoint-derived preferences, relative importance by performing multivariable regression to identify predictors of transfusion preferences was assessed.


RESULTS
A total of 350 providers completed the survey (n=305 nephrologists; mean age=46 years; 21% women). Of 10 attributes assessed, absolute hemoglobin level was the most important driver of transfusions, accounting for 29% of decision-making, followed by functional status (16%) and cardiovascular comorbidities (12%); 92% of providers transfused when hemoglobin was 7.5 g/dl, independent of other factors. In multivariable regression, Veterans Administration providers were more likely to transfuse at 8.0 g/dl (odds ratio, 5.9; 95% confidence interval, 1.9 to 18.4). Although transplant eligibility explained only 5% of decision-making, nephrologists were five times more likely to value it as important compared with non-nephrologists (odds ratio, 5.2; 95% confidence interval, 2.4 to 11.1).


CONCLUSIONS
Adaptive choice-based conjoint analysis was useful in predicting influences on transfusion decisions. Hemoglobin level, functional status, and cardiovascular comorbidities most strongly influenced transfusion decision-making, but preference variations were observed among subgroups.
Departments of Research and, ¶Internal Medicine, Veterans Administration Greater Los Angeles Healthcare System, Los Angeles, California;, †University of California at Los Angeles, Veterans Administration Center for Outcomes Research and Education, Los Angeles, California;, ‡Global Health Economics, Amgen, Inc., Thousand Oaks, California;, §Department of Internal Medicine, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, California, ‖Department of Health Services, University of California at Los Angeles School of Public Health, Los Angeles, California.
Cynthia B
CB
Whitman
Sanatan
S
Shreay
Matthew
M
Gitlin
Martijn G H
MG
van Oijen
Brennan M R
BM
Spiegel
D000368:Aged; D000369:Aged, 80 and over; D000740:Anemia / Q000097:blood / Q000175:diagnosis / Q000209:etiology / Q000628:therapy*; D015415:Biomarkers / Q000097:blood; D015897:Comorbidity; D003661:Decision Support Techniques; D017707:Erythrocyte Transfusion / Q000009:adverse effects; D005260:Female; D019538:Health Care Surveys; D006304:Health Status; D006454:Hemoglobins / Q000378:metabolism; D006801:Humans; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D016017:Odds Ratio; D018579:Patient Selection; D010818:Practice Patterns, Physicians'; D006435:Renal Dialysis / Q000009:adverse effects; D051436:Renal Insufficiency, Chronic / Q000097:blood / Q000175:diagnosis / Q000628:therapy*; D018570:Risk Assessment; D012307:Risk Factors; D012720:Severity of Illness Index; D011795:Surveys and Questionnaires
D015415:Biomarkers; D006454:Hemoglobins