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Keywords:

  • leukemia;
  • working memory;
  • attention;
  • leukoencephalopathy;
  • intelligence

Abstract

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. CONFLICT OF INTEREST DISCLOSURES
  8. REFERENCES

BACKGROUND:

To extend investigation beyond global cognitive measures prevalent in the literature, this study examined attention and working memory (WM) abilities of survivors of childhood acute lymphoblastic leukemia (ALL), the separate contributions of attention and WM to intelligence quotient (IQ), and their association with neuroimaging changes.

METHODS:

Ninety-seven children with ALL received risk-directed therapy based on presenting clinical and biological factors. During consolidation therapy, low-risk patients received half the dose of intravenous methotrexate that standard-risk/high-risk patients received, and fewer doses of triple intrathecal therapy. Patients were classified according to end of consolidation magnetic resonance imaging scans (normal or leukoencephalopathy), and continuous measures of white matter structure were computed. As part of the protocol study, children completed cognitive assessment 2 years later (completion of therapy), using Digit Span Forward (DSF) for attention and Digit Span Backward (DSB) for WM.

RESULTS:

For the total sample and the standard-/high-risk group, Total Digit Span (TDS), DSF, and DSB were impaired relative to norms (P <.05). In the low-risk group, only DSB was impaired (P <.0001). Across groups, a higher percentage of patients performed below the average range (scale score <7) on DSB (66%) compared with the DSF (14%) or TDS (18%). Regression analysis indicated that DSB predicted estimated IQ (P <.05), after accounting for DSF. Leukoencephalopathy was predictive of lower TDS (P <.05).

CONCLUSIONS:

WM appears to be especially sensitive to treatment-related changes in ALL survivors, detecting difficulties potentially missed by global intelligence measures. These findings may facilitate the identification of vulnerable neural pathways and the development of targeted cognitive interventions. Cancer 2010. © 2010 American Cancer Society.

Acute lymphoblastic leukemia (ALL) is the most common malignancy of childhood and adolescence, with this age group comprising approximately two-thirds of the 4000 total cases diagnosed annually in the United States. Over the past few decades, there have been significant improvements in ALL treatment outcomes, resulting in 5-year event-free survival rates of nearly 90%.1 Increased cure rate has led to increased attention to the quality of life of these survivors.

Although recent treatment regimens are associated with decreased adverse side effects, including cognitive late effects, ALL survivors are still subject to increased cognitive impairments secondary to disease and treatment.2 Historically, cognitive outcomes have been evaluated using global measures assessing abilities such as intelligence quotient (IQ) and academic achievement. These studies typically indicate that healthy controls perform better on these benchmarks than children treated for ALL.3 Recent research has begun to examine more specific and functional cognitive processes. For example, deficits in attention,4 problems with attention and memory,5 and decreased processing speed and working memory (WM)6 have been demonstrated in ALL survivors.

Curative therapy for ALL includes central nervous system (CNS) -directed therapy, generally in the form of intensive systemic and intrathecal chemotherapy. Prophylactic CNS irradiation had been part of the standard treatment historically, but is now generally limited to patients with high-risk ALL and is omitted for all patients in some protocols.1 However, systemic and intrathecal chemotherapy can also cause neurocognitive deficits and cerebral white matter changes. Reddick et al7 determined that smaller white matter volumes observed in ALL survivors are associated with declines in attention, intelligence, and academic achievement.

The frontal lobes of the brain are the last to fully develop with respect to cerebral white matter, with myelination extending into the third decade of life.8-10 Given this protracted development, cognitive processes supported by the frontal lobes (eg, attention and WM) may be particularly vulnerable to the neurotoxicities associated with CNS-directed therapy. A significant proportion of age-related improvements in IQ can be accounted for by developmental improvements in WM.11 These neuroanatomic developmental trajectories, together with the established declines in the intelligence of ALL survivors, warrant a detailed examination of attention and WM to elucidate potentially vulnerable neural pathways.

To examine these specific cognitive constructs, the current study explored the attention and WM abilities of childhood ALL survivors. The study also investigated the unique contribution that attention and WM make to IQ. Finally, the association between these abilities and treatment-related white matter changes was analyzed. Based on the existing literature, we hypothesized that these survivors would demonstrate deficits in the areas of intelligence and attention but with the most significant decreases noted in WM. We also expected that WM would be significantly associated with overall intellectual functioning. Finally, we anticipated a relation between higher levels of leukoencephalopathy and decreased WM.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. CONFLICT OF INTEREST DISCLOSURES
  8. REFERENCES

Patients

All patients in the current study were sequentially enrolled on a frontline institutional ALL treatment protocol that included serial cognitive assessment.1 Children were assigned to 1 of 3 risk groups (low, standard, or high) based on comprehensive biological and clinical risk classification, which included blast cell immunophenotype and genotype, presenting clinical features, and early treatment response.1 All patients received triple intrathecal therapy with methotrexate, hydrocortisone, and cytarabine as CNS-directed therapy (13 to 18 treatments in the low-risk group and 16 to 25 treatments in the high-risk group), beginning with remission induction therapy. During consolidation therapy, high-dose methotrexate was given intravenously every other week for 4 doses at 2.5 g/m2 per dose for low-risk patients and at 5.0 g/m2 for standard-risk/high-risk patients. None of the patients received prophylactic cranial irradiation. During continuation treatment, dexamethasone pulses were given at 8 mg/m2 per day for low-risk patients, and at 12 mg/m2 per day for standard-risk/high-risk patients.

For the purposes of this study, all children between the ages of 6 and 18 years were included in analyses based on the normative ranges for cognitive measures. Children were further excluded from analysis if they were previously diagnosed with a developmental disorder with known cognitive sequelae (Down syndrome or autism; n = 6), did not speak English (n = 14), or were missing imaging and/or psychological testing data (n = 54; these included children with refractory or progressive disease, missed testing appointments, scheduling problems, or technical issues interfering with imaging acquisition). The study was approved by the Institutional Review Board. Written informed consent, with assent from the patient, as appropriate, was obtained before participation. Study enrollment occurred between 2000 and 2007.

Procedures

Cognitive assessment

Children were tested 2 years after the completion of consolidation therapy (Week 120) using measures standardized on large representative normative samples that have demonstrated reliability and validity.12, 13 They were administered an age-appropriate Wechsler Intelligence Scale (Wechsler Intelligence Scale for Children-Third Edition [WISC-III] for patients aged <16 years and Wechsler Adult Intelligence Scale-Third Edition [WAIS-III] for patients aged ≥16 years). The current study focused primarily on the Digit Span (DS) subtest, which yields age-standardized scores for Total Digit Span (TDS), Digit Span Forward (DSF), and Digit Span Backward (DSB). For DSF, which is regarded as a measure of attention and immediate recall, the examiner verbally presents specified random sequences of digits that the participant is required to repeat back verbatim. For DSB, the participant must reverse the order of the digits before repeating. Given this additional requirement to mentally manipulate information, this task is conventionally considered a measure of verbal WM.14, 15 TDS is the aggregate of DSF and DSB.

In addition to the DS subtest, an estimated IQ (EIQ) was also derived for each participant at study baseline and Week 120. This score is computed from the Information, Similarities, and Block Design subtests from either the WISC-III or WAIS-III using a formula provided by Sattler.16 The EIQ was chosen over the Full-Scale IQ (FSIQ) because DS scores are included in the determination of FSIQ. Thus, EIQ provides a valid and reliable estimate of IQ that can be tested for relations to attention and WM without the embedded measures of these constructs.

Magnetic resonance imaging

Conventional magnetic resonance imaging (MRI) was performed on 1 of 2 1.5 Tesla (T) whole-body MR systems using the standard circular polarized volume head coil (Avanto; Siemens Medical Systems, Iselin, NJ). Leukoencephalopathy, T2-hyperintensities within the white matter, is best visualized with a T2-weighted sequence, preferably with cerebrospinal fluid attenuated. Imaging was acquired and included at least 19 oblique 4 mm-thick axial images with a 1-mm gap. T1-weighted images were acquired with a multi-echo inversion recovery sequence (repetition time between spin excitations [TR] = 8000 milliseconds [ms]; echo time [TE] = 20 ms; time between inversion and the excitation pulse [TI] = 300 ms; 11 echoes). The T2/proton density-weighted images were acquired with a dual spin-echo sequence (TR/TE1/TE2 = 3500/17/102 ms, 7 echoes). Fluid-attenuated inversion recovery images were acquired with a multiecho inversion recovery sequence (TR/TE/TI = 9000/119/2470 ms; 11 echoes). These imaging sets covered most of the cerebrum starting at the apex of the brain but did not include the cerebellum.

Patients were classified according to MRI images (normal or leukoencephalopathy) at the completion of consolidation therapy based on retrospective review by a single neuroradiologist (F.H.L.) blinded to results of cognitive assessment. Volumes of regional brain parenchyma on MRI images were quantified using an automated hybrid neural network segmentation and classification method.17 Robust reliability and validity have been established for these methods, resulting in a predicted variance of approximately 2% in the repeated measures of normal-appearing white matter (NAWM) and gray matter.18 Once each examination was segmented, we assessed the extent of leukoencephalopathy and volume of NAWM in left/right and anterior/posterior quadrants. Volumes were assessed both as absolute volumes in cubic centimeters and relative volumes for which each tissue's volume was normalized to the intracranial volume.

Statistical Analyses

To characterize the sample, qualitative analyses of demographic and clinical variables were performed. Demographic and clinical variables were also examined to investigate potential associations with measures of attention and WM.

The extent of cognitive impairment was estimated by comparing the performance of ALL survivors on EIQ and the DS tasks to the normative population (EIQ has a mean of 100 and standard deviation [SD] of 15; DS scaled scores have a mean of 10 and a SD of 3) using 2-tailed 1-sample Student t tests. Performance on the DS tasks was also examined to determine the rate of clinical impairment by investigating the percentage of patients who scored at least 1 standard deviation below the mean for TDS, DSF, and DSB. Multiple linear regression analysis was used to analyze the contribution of DSB to EIQ after accounting for DSF.

Finally, to examine possible effects of neuroanatomic findings, the dichotomous neuroradiologist ratings (normal or leukoencephalopathy) were examined for their relation to performance on the DS task using Wilcoxon rank 2-samples tests. To further investigate these clinical measures, correlations among continuous metrics of white matter structure (absolute and relative NAWM and leukoencephalopathy volumes) and performance on the DS task were conducted. Each of the above analyses was performed across the total patient population as well as with risk-based subgroups (ie, standard-/high- and low-risk).

RESULTS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. CONFLICT OF INTEREST DISCLOSURES
  8. REFERENCES

Demographic and Clinical Characteristics

Ninety-seven children (55 males and 42 females) were included in this study. The ethnicity of the sample was representative of the overall treatment protocol population. On average, children were 8 years old at diagnosis and 10 years old at assessment, with a baseline EIQ of 100. Treatment risk arm assignment was nearly equal, with 48 patients classified as low-risk and 49 patients classified as standard-risk or high-risk. Demographic and clinical characteristics are summarized in Table 1.

Table 1. Patient Demographic and Clinical Characteristics
Characteristic No.%
  • SD indicates standard deviation; EIQ, estimated intelligence quotient.

  • a

    Assessment performed 2 years after the completion of consolidation therapy (Week 120).

  • b

    IQ was estimated using the Wechsler Intelligence Scale for Children-Third Edition (WISC-III)/Wechsler Adult Intelligence Scale-Third Edition (WAIS-III) Similarities, Information, and Block Design subtests.

  • c

    Sample size discrepancy was due primarily to patients being too young for assessment at baseline.

Gender   
 Male 5556.7
 Female 4243.3
Ethnicity   
 Caucasian 7173.2
 African American 2020.6
 Other 66.2
Risk arm   
 Standard/high 4950.5
 Low 4849.5
 No.Mean ± SDRange
Age at diagnosis, y978.22±3.933.46-18.45
Age at assessment, ya9710.84±3.936.02-21.00
Baseline EIQb65c100.92±16.5458-138

No statistical associations were found between demographic variables and attention or WM performance. Of the clinical variables, only risk classification demonstrated an association with attention and WM ability, with standard-risk/high-risk patients performing significantly worse (P <.01) on TDS compared with low-risk patients. This relation is explored.

Attention and WM Performance

Patients' performance on neuropsychological measures in relation to the normative sample is summarized in Table 2. Across the entire sample, EIQ at Week 120 did not differ significantly when compared with the normative mean of 100. There was also no statistical departure from the norm for EIQ for standard-risk/high-risk or low-risk patients. In addition, Week 120 EIQ did not differ significantly from baseline EIQ. This was true of the entire sample and for individual risk groups.

Table 2. Neuropsychological Variables in Relation to Normative Data
VariableNo.Mean ± SDPa
  • SD indicates standard deviation; EIQ, estimated intelligence quotient; DS, Digit Span; DSF, Digit Span Forward; DSB, Digit Span Backward.

  • a

    Tested for significant difference from mean of normative sample (DS standard score, 10±3; EIQ, 100±15).

  • b

    P <.05.

  • c

    Twelve patients were aged >16 years and received the Wechsler Adult Intelligence Scale-Third Edition (WAIS-III), which does not provide separate standard scores for DSF and DSB.

Week 120 EIQ   
 All patients95100.4±17.34.8226
 Standard-/high-risk4896.88±18.46.2469
 Low-risk47104.00±15.49.0832
Total DS standard score   
 All patients978.81±2.89.0001b
 Standard-/high-risk497.92±2.67<.0001b
 Low-risk489.73±2.85.5134
DSF standard score   
 All patients85c9.28±2.68.0157b
 Standard-/high-risk418.66±2.82.0040b
 Low-risk449.86±2.45.7133
DSB standard score   
 All patients85c5.79±2.46<.0001b
 Standard-/high-risk415.29±2.30<.0001b
 Low-risk446.25±2.54<.0001b

For the sample as a whole, patients demonstrated significant impairment on TDS, DSF, and DSB (P <.05) in comparison with the normative mean of 10. Standard-risk/high-risk patients demonstrated the same pattern, with deficits across all tasks (P <.01). In contrast, the low-risk group demonstrated significant impairment only on DSB (P <.0001) and maintained statistically normal performance on TDS and DSF. This finding suggests that WM (as measured by DSB) may be particularly sensitive because it was impaired in patients with the lowest treatment intensity.

Patients' performance on the DS tasks was defined as clinically significant if the score fell below 1 standard deviation from the normative mean (<7) and therefore outside the average range (Figure 1). Across the entire sample, a high percentage of patients fell below this clinical cutoff on DSB (65.9%), whereas expected proportions of children demonstrated this impairment on TDS (17.5%) and DSF (14.1%). The same pattern of clinical significance was noted in the standard-risk/high-risk group (TDS, 24.5%; DSF, 19.5%; and DSB, 70.7%) and the low-risk group (TDS, 10.4%; DSF, 9.1%; and DSB, 61.4%).

thumbnail image

Figure 1. Patients with clinically significant digit span (DS) deficits are shown, demonstrating the percentage of patients who score clinically below average on DS tasks. ss indicates standard score.

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Regression analysis was used to determine the degree to which DS tasks predict EIQ and investigate whether DSB made a unique contribution after DSF was taken into account. A scatterplot of these analyses can be found in Figure 2. Results indicated that 21% of the variance of EIQ is explained by DSF and DSB. Further analysis indicated that DSB still contributed significantly (P = .01) after accounting for DSF (P = .01). These results suggest that WM is a unique aspect of overall intelligence over and above attention.

thumbnail image

Figure 2. Contributions of Digit Span Forward (DSF) and Digit Span Backward (DSB) to intelligence quotient (IQ) are shown, using a scatterplot reflecting regression analysis examining the degree to which DS tasks predict estimated IQ (EIQ). ss indicates standard score.

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Neuroanatomic Changes

Performance on the DS tasks was also related to neuroanatomic findings. Examination of the dichotomous neuroradiologist ratings (normal vs leukoencephalopathy) of patient MRIs revealed that children with normal ratings had significantly better scores on TDS (P = .03) across all patients. Results in the low-risk group were similar (P = .01), but this pattern was not noted in the standard-risk/high-risk group alone. To further investigate this relation, continuous variables of white matter structure were assessed. Neither the absolute nor the relative NAWM volumes were found to be significantly associated with performance on the DS task. However, greater absolute volumes of leukoencephalopathy in all 4 quadrants (left/right, anterior/posterior) were found to be significantly associated with lower scores on TDS (both anterior, P = .01; both posterior, P = .04) across all patients. Results in the low-risk group were similar (both anterior, P = .01; both posterior, P = .02), but this pattern was not noted in the standard-/high-risk group alone.

To ensure that this relation was not related to patient head size, we also assessed relative volumes. The same associations were demonstrated, with greater relative volumes of leukoencephalopathy in all quadrants being significantly associated with lower scores on TDS across all patients (both anterior, P = .01; both posterior, P = .04) and for the low-risk group (both anterior, P = .01; both posterior, P = .02) but was not observed for the standard-risk/high-risk group.

DISCUSSION

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. CONFLICT OF INTEREST DISCLOSURES
  8. REFERENCES

Results from this study revealed that, 2 years after completing therapy, childhood ALL survivors demonstrate impairment in WM, suggesting that WM is particularly sensitive to ALL treatment regimens. Although the standard-risk/high-risk group demonstrated impairment in attention and WM, only deficits in WM were detected in the low-risk group. In addition, these effects on WM proved clinically meaningful, with a large percentage of children functioning below the average range. Taken together, we can conclude that WM is sensitive to current treatment regimens despite risk-adapted treatment stratification of patients and reduction in the use of neurotoxic agents.

In addition to being particularly sensitive, WM proved to be a unique contributor to overall intellectual functioning. After accounting for attention, WM still played a significant role in predicting IQ. This study gives evidence to WM as a distinct aspect of overall intelligence of ALL survivors. Given the established contributions of WM to developmental improvements in intelligence, WM may therefore be a proximal contributor to previously identified IQ declines in these children.

Treatment-induced white matter changes proved to be associated with a decrease in attention and WM. Using both dichotomous ratings (normal and leukoencephalopathy) and continuous measures of white matter structure, children with leukoencephalopathy scored lower on combined attention and WM tasks. It appears that these neuroanatomic changes are related to decreased abilities in these ALL survivors. In addition, because imaging was obtained at the end of consolidation therapy and cognitive assessment occurred 2 years later, there appears to be a predictive nature to this relation. These findings were statistically significant for the low-risk patients and trending in the same direction for patients in the standard-risk/high-group. This risk-stratified finding could be explained by the older age of standard-risk/high-risk patients. Given more mature white matter, these children may not have suffered as much leukoencephalopathy as younger patients with less myelination.

The study found that WM played a significant role in predicting IQ and that there were significant deficits in WM within our sample. However, in what appears to be a contradictory finding, no IQ deficits were observed in relation to the normative population or baseline intellectual functioning. This finding is also in contrast to prior studies indicating global declines after therapy for ALL.7, 5, 19, 20 This is likely due to the use of EIQ instead of FSIQ. Although we were able to demonstrate the importance of WM to overall intellectual functioning (as EIQ is highly representative of FSIQ), the selected subtests used in this study (Information, Similarities, and Block Design) are not heavily reliant on WM abilities or processing speed. Therefore, EIQ scores may not have been impacted as were FSIQ scores containing WM or processing speed subtests, abilities shown to be at risk in this population.6 It should also be remembered that many treatment refinements have taken place since these prior studies. A part of the IQ resiliency may be due to the protection offered by newer therapy regimens. The current study did find global declines in attention (as measured by TDS), similar to those in the established literature.4

As a result of using the Wechsler tests as measures of intelligence and WM, we were unable to assess the youngest children in our sample (because it is not normed for children aged <6 years) and patients aged >16 years were not included in the WM analyses (due to lack of standard scores for DSF and DSB on the WAIS-III). This truncated age range may have limited our ability to detect age effects of treatment on attention or WM. This lack of age effects is inconsistent with current literature demonstrating that patients who are younger at treatment have poorer neurocognitive outcomes.21 It should be noted that, because of the longitudinal nature of our data, most of the children who were too young for inclusion at baseline were old enough for assessment 2 years later. The inclusion of multiple WM measures in future studies would allow assessment of a wider age range of patients and provide a more comprehensive picture of WM skills.

With regard to neuroanatomic findings, the literature is very consistent in placing the mediation of executive tasks (including WM) in the frontal and prefrontal cortex.22-24 These brain regions are the last to myelinate and therefore may be particularly vulnerable to insults related to CNS-directed therapies. Accordingly, it was hypothesized that white matter changes associated with decreased WM would be located in the anterior portions of the brain. This hypothesis was not confirmed because identical correlations were found between WM performance and posterior brain regions. One explanation for this finding is that the division of the brain into quadrants for analysis is not based on anatomic or functional regions, and thus the anterior portions do not represent specific areas within the frontal and prefrontal cortex (eg, the dorsal lateral prefrontal cortex). Another likely confounding factor is the presence of longitudinal nerve fibers. Even when assessing performance of functional regions within the frontal cortex, long associational fibers connect these regions with more distant cortical and thalamic regions.25, 26 These fibers may span both the anterior and posterior regions of interest and, thus, make the observed measures abnormal across multiple regions. Subsequent studies should take advantage of diffusion tensor imaging to more specifically investigate the role and location of white matter changes associated with cognitive changes.

Future studies could benefit from expansion and improvement on the current design as we continue to investigate WM abilities in ALL survivors. We believe that the use of a predictive (vs concurrent) design of the current study gives further weight to the finding that early detected leukoencephalopathy can serve as a warning of later cognitive declines. As demonstrated in Table 3, only a small percentage of patients will develop leukoencephalopathy if these changes are not present at the end of consolidation therapy. Although a larger portion of patients demonstrate resolution of white matter changes, as reported previously,27, 28 the current study was concerned with the early identification of children at risk for the later development of cognitive deficits. Additional longitudinal testing points to assess the persistence or exacerbation of deficits over time would also be beneficial and use of a non-CNS cancer control group would serve to further illustrate the effects of CNS-directed treatment. In addition to the use of diffusion tensor imaging, functional MRI techniques may identify changes in resource allocation during task performance.

Table 3. Change in MRI Classification of White Matter Between End of Consolidation and End of Therapy
MRI 1 ClassificationMRI 2 ClassificationChange in Status%
  1. MRI indicates magnetic resonance imaging; MRI 1, images obtained at the end of consolidation therapy; MRI 2, images obtained at the end of therapy.

Normal67Normal59Unchanged95%
  Abnormal3Late change5%
  Missing5  
Abnormal26Normal6Resolved25%
  Abnormal18Persistent75%
  Missing2  
Missing4Normal4 100%
  Abnormal0  
  Missing0  
Total93 90  

A major implication of these findings is that treatment-related neurocognitive deficits may be more subtle than detectable by global measures of intelligence and achievement. If the medical team relies on the more common global assessments, these more specialized cognitive deficits may be missed. Given what we know about the developmental contribution of WM to overall intelligence,11 it may also be that unidentified WM deficits may result in later emerging IQ and academic achievement problems. With these vulnerable pathways in mind, treatment planning for ALL can be more cognizant of early indications of leukoencephalopathy. If the acute neuroimaging changes (ie, leukoencephalopathy) are associated with later emerging deficits in attention and WM, chemotherapy regimens may be adjusted to provide greater sparing of these sensitive areas. Modern ALL therapy has largely eliminated CNS radiotherapy as a frontline therapy for newly diagnosed patients, and therapy continues to evolve. Decreased dosages of corticosteroids and fewer intrathecal therapies across the span of treatment are examples of measures being put in place to help alleviate adverse side effects associated with CNS-directed therapy.

It is important to educate parents about the potential for attention and WM deficits to emerge subsequent to ALL treatment. They should know that “low-risk” does not equal “no risk,” because even at the lowest intensity, these CNS-directed agents can still have significant effects on their child's cognitive functioning. Proactive education of families will allow for closer monitoring and earlier intervention should problems arise.

In addition to the reduction of cognitive late effects through treatment advances, there is encouraging emerging support for interventions that may mitigate the impact of cognitive sequelae that may not be entirely unavoidable. In addition to well-established pharmacologic interventions,29, 30 there are cognitive remediation programs currently being evaluated that demonstrate promise for improving attention and WM.31 Ideally, this will help to synchronize the improved disease-related outcomes with long-term quality of life outcomes for children cured of ALL.

Acknowledgements

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. CONFLICT OF INTEREST DISCLOSURES
  8. REFERENCES

We thank the patients and their families who volunteered their time to participate.

CONFLICT OF INTEREST DISCLOSURES

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. CONFLICT OF INTEREST DISCLOSURES
  8. REFERENCES

Supported in part by the Cancer Center Support (CORE) Grant (P30 CA21765 and R01 CA90246 to W.R.) from the National Cancer Institute and by the American Lebanese Syrian Associated Charities (ALSAC).

REFERENCES

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. CONFLICT OF INTEREST DISCLOSURES
  8. REFERENCES
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