3.4 | Follow-up Care Analysis
Of the 865 survivors included in the final analytic cohort, 282 (32.6%)
were not seen in any oncology-related subspecialty clinic (PHO, PNO,
PBMT, Medical Oncology) five to seven years after the initial diagnosis.
Factors associated with follow-up included risk strata (0.001), age
(p=0.008), primary diagnosis (p<0.001), and race/ethnicity
(p=0.010). Risk strata was the primary association of interest for this
analysis. Low risk patients yielded the highest follow-up with 78% of
patients, followed by high risk patients at 70%, and intermediate risk
patients at 63%. To include spatial data elements, we restricted
analysis to survivors within NC, SC, and VA (n=787). Similar
associations with follow-up patterns were observed as well as lower ADI
national percentile (p=0.011) and distance to primary treatment site
(p<0.0001), though not distance to a COG-affiliated site
(p=0.729) (Table 2). Manual chart review of a 10% randomized sample of
patients lost to follow-up from each risk strata (n=37) revealed that
most patients were instructed to follow-up; however there was no
additional follow-up documented in EHR. One low risk, four intermediate
risk, and no high risk patients had documentation of care transferred to
another institution.
We first built a logistic model to test the unadjusted association
between risk stratification and appropriate follow-up care through a
likelihood ratio test (LRT). There was strong evidence
(p<0.001) that there was an association between risk
stratification and follow-up care (Table 3). Pairwise comparisons showed
that the odds of receiving follow-up in the five to seven year window
after initial diagnosis in the intermediate risk strata was half the
odds of receiving follow-up in the low risk strata (OR 0.482; CI 0.3,
0.774, p<0.001). However, there is insufficient evidence to
suggest the odds of follow-up is different in pairwise comparisons
between high and intermediate risk and high and low risk survivors
(p=0.41 and p=0.23, respectively). We then built a multiple logistic
regression model adjusted for diagnosis of ALL, gender, age at
diagnosis, race/ethnicity as potential confounders. This attenuated the
observed association and, after controlling for potential confounding,
there was insufficient evidence to suggest there is an association
between risk strata and follow-up care (p=0.17) (Table 4).
To test the hypothesis that risk strata may have a different effect if
the patient is closer to the primary treatment center (i.e. Duke), we
created a model that included the interaction between local residence
and risk strata and used a lack of fit test to look for evidence that
living in NC, SC or VA modified the effect of risk strata. There was
insufficient evidence (p=0.14) to suggest that “local” patients
modified the risk strata effect on likelihood to follow-up in the five
to seven year window. For the survivorship cohort limited to NC, SC, and
VA, we then constructed a multiple logistic regression model to adjust
for ALL, gender, age at diagnosis, race/ethnicity as well as ADI,
distance to primary treatment center, distance to COG-affiliated site,
and RUCA. This yielded similar results with attenuation of the initially
observed associated between follow-up care and risk strata, thus there
was insufficient evidence to suggest an association between risk strata
and follow-up care in the five to seven year window after the initial
diagnosis (p=0.11) (Table 4).