Study strengths

The strengths of this dissertation outweigh its limitations. The primary strength of this dissertation was our statistical approach. We attempted to overcome confounding by indication/disease severity (i.e., sicker patients receive more treatment) and other methodological issues commonly present in non-experimental studies conducted at the individual-level with our statistical approach. We adopted a statistical approach aimed at minimizing confounding due to unmeasured variables that directly influence the decision to administer vitamin D and confounding due to the fact that patients prescribed vitamin D may be fundamentally different from those who are not administered the drug. Confounding bias may be attenuated or even eliminated with the use of an ecological, grouped-treatment variable that is related to the patient’s treatment but weakly associated with unmeasured patient risk factors.215

Researchers have longed cautioned against the use of ecological studies to make inferences at the individual-level in a phenomenon known as the ecologic fallacy.216 Associations found at an aggregated unit of analysis may not necessarily hold true at the individual-level.216 However, in the presence of confounding at the individual-level, the relative immunity of ecological studies to confounding by indication may supersede any ecologic fallacy issues if variation in treatment utilization is driven by differences in practice

style.121, 216 To circumvent the deficits of ecological studies and to take advantage of the relative immunity of the approach from confounding by indication, we employed the

grouped-treatment approach. Vitamin D use and dose were aggregated to the dialysis facility- level while covariates and fracture outcomes were measured at the patient-level.188

Confounding by indication bias was mitigated with the ecological treatment variable and we capitalized on the advantages of increased precision with observed confounders and

outcomes at the individual-level.124

We recognized that residual confounding may still persist, even after aggregating vitamin D treatment to the facility-level. Our key vitamin D variables may have been

confounded by demographic and clinical attributes of patients at a particular facility that may have influenced how that center decided to administer vitamin D. It was important to ensure that our measurement of vitamin D exposure at the facility-level was capturing variations in vitamin D use and dose at a facility, independent of that facility’s patient case-mix. A facility’s high use of vitamin D may actually reflect a clustering of patient’s with a

preponderance of characteristics that merit higher vitamin D dosage. For instance, a facility may serve a preponderance of black hemodialysis patients, generally administered higher doses of vitamin D compared to patients of other races.186 To this end, an additional strength of this dissertation was that we addressed this potential bias by creating case-mix adjusted measures of vitamin D exposure that reflected a facility’s propensity to prescribe vitamin D given the facility’s patient population.

Our target population of hemodialysis facilities was a considerable strength. The validity of our approach is contingent upon the assumption that the pre-treatment prognosis of patients is not associated with the proportion of patients treated with vitamin D at a

dialysis facility.212 By way of explanation, the assumption relies on the fact that high-risk patients are not being transferred to particular dialysis facilities because of that facility’s vitamin D utilization practices. Studies of dialysis facilities provide a unique opportunity to plausibly fulfill this rather restrictive assumption. Unlike hospitals where patients are most often referred to the hospital most adept at providing the particular procedure or care needed, dialysis patients generally attend the dialysis center in closest geographical proximity to their residence. Therefore, the vitamin D treatment practices of a dialysis facility do not play a role in the decision to attend a particular facility, providing us with the basis for a natural experiment and pseudo-randomization.

Another strength of this dissertation was the use of a proxy for functional status to account for waning underlying health processes that may predict fracture risk. Functional status was estimated using claims for personal assistance aids like wheelchairs, canes, walkers, and modified bathroom equipment. Patients with ESRD experience many of the clinical manifestations of frailty found in patients without kidney disease such as declining physical function, comorbidities, and loss of muscle mass.153 Adverse outcomes like

hospitalizations and death have been shown to be mediated by frailty153, but few prior studies have attempted to control for its possible effects.

Additionally, this dissertation is unique in its exploration of different subgroups and multiple fracture types. Study 1 explored temporal trends in vitamin D use and dosing by relevant subgroups. Study 2 investigated the association between vitamin D exposure and fracture outcomes by fracture type and relevant subgroups. Unlike our study, the Dialysis Outcomes and Practice Patterns Study (DOPPS), the most contemporary report of IV vitamin D use and dose in the United States, did not report variations in vitamin D use by race, age,

and sex subgroups and used a small sample size of less than 4,000 patients.183 Studies examining the incidence and factors associated with fracture risk have focused

predominantly on hip fracture and were based on selective groups of patients.73, 74, 77, 82-84 Our study assessed the association between vitamin D exposure and fracture by four fracture categories that represented the most clinically significant and costly types.

Our use of USRDS files is the final major strength of this dissertation. The USRDS captures data on every ESRD patient in the United States and contains the most detailed data on demographic attributes, diagnoses, treatment histories, hospitalizations and dialysis facility services.217 Our population-based study had a large sample size of over 130,000 patients representing over 4,000 dialysis facilities nationwide.