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\begin{document}

\title{TITLE PAGE: NEUROCOGNTIVE OUTCOMES IN SURVIVORS OF CHILDHOOD ACUTE
LYMPHOBLASTIC LEUKEMIA: EXPERIENCE FROM A TERITARY CARE CENTRE IN INDIA}



\author[1]{Vishwa  CR}%
\author[1]{Gargi Das}%
\author[1]{Rachna Seth}%
\author[1]{Savita  Sapra}%
\author[1]{Prasanth Siri}%
\author[1]{Jagdish Meena}%
\author[2]{Aditya Gupta}%
\author[3]{Sreenivas Vishnubhatla}%
\affil[1]{All India Institute of Medical Sciences}%
\affil[2]{Childrens Hospital at Westmead}%
\affil[3]{AIIMS, New Delhi}%


\vspace{-1em}



  
  \date{June 05, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
BACKGROUND: Neurocognitive deficits are an important late effect in
survivors of acute lymphoblastic Leukemia(ALL). Data from low middle
income countries is scarce and highly influenced by biological and
cultural variations. Such data would be useful for highlighting the
importance of early intervention in an already disadvantaged population.
PROCEDURE: 70 consecutive survivors of childhood ALL were evaluated for
neurocognitive deficits by the Indian adaptation of Wechsler
Intelligence Scale for Children-Fourth Edition(WISC-INDIA). Prevalence
of neurocognitive deficits was calculated based on Full Scale
Intelligence Quotient(FSIQ) and scores in discrete domains like Verbal
Comprehension, Perceptual Reasoning, Working Memory and Processing Speed
were calculated and compared to baseline characteristics, chemotherapy
and radiation dose received. RESULTS: The mean FSIQ was 86.1 \selectlanguage{ngerman}± 20.5,
with significant neurocognitive deficit(FSIQ \textless{}90) being
prevalent in 50\%(95\% CI 38\% to 62\%) of the cohort. The proportion of
survivors with deficits in individual domains of verbal comprehension,
perceptual reasoning, working memory and processing speed were 49\%,
50\%, 47\% and 44\% respectively. The odds of having deficits in
neurocognitive function was higher when a child belonged to lower
socioeconomic strata, had parents with less than primary school
education and whose birth order was higher(All p\textless{}0.05). Age at
diagnosis, current age at assessment, receiving lower or higher dose of
radiotherapy, high dose methotrexate or cytarabine did not have a direct
impact on neurocognitive function. CONCLUSIONS AND RELEVANCE: The
current need is to develop country specific neurocognition assessment
tools to initiate early screening and develop culturally appropriate
preventive and rehabilitative interventions.%
\end{abstract}\selectlanguage{ngerman}%



\sloppy


\textbf{TITLE PAGE: NEUROCOGNTIVE OUTCOMES IN SURVIVORS OF CHILDHOOD
ACUTE LYMPHOBLASTIC LEUKEMIA: EXPERIENCE FROM A TERITARY CARE CENTRE IN
INDIA}

\textbf{Author details}

Corresponding author

\begin{enumerate}
\tightlist
\item
  Dr Rachna Seth, Professor, All India Institute of Medical Sciences-New
  Delhi.
\item
  Email: drrachnaseth1967@gmail.com
\item
  Postal Address: Room 3603, Division of Pediatric Oncology, Department
  of Pediatrics, 3\textsuperscript{rd} floor, Academic Block, AIIMS-New
  delhi, 110029.
\item
  Telephone: +91 9971188687, 011 - 2659 3209, 011 - 26694345
\item
  Fax: 011 -- 2658 8663
\end{enumerate}

Authors

\begin{enumerate}
\tightlist
\item
  Dr Vishwa CR, MD Pediatrics, All India Institute of Medical
  Sciences-New Delhi. crvishwacr@gmail.com.
\item
  Dr Gargi Das, DM Fellow, Pediatric Oncology, All India Institute of
  Medical Sciences-New Delhi. gargi.das.17@gmail.com.
\item
  Dr Rachna Seth, Professor, All India Institute of Medical Sciences-New
  Delhi. drrachnaseth1967@gmail.com.
\item
  Dr Savita Sapra, Professor, Child Psychology, All India Institute of
  Medical Sciences-New Delhi. saprasavita@yahoo.com.
\item
  Dr Prasanth Sri, DM Fellow, Pediatric Oncology, All India Institute of
  Medical Sciences-New Delhi. prasanth230591@gmail.com.
\item
  Dr Jagdish Prasad Meena, Associate Professor, All India Institute of
  Medical Sciences-New Delhi. drjpmeena@gmail.com.
\item
  Dr Aditya Kumar Gupta, Assistant Professor, All India Institute of
  Medical Sciences-New Delhi. adivick@gmail.com.
\item
  Dr V Sreenivas, Professor, Biostatistics, All India Institute of
  Medical Sciences-New Delhi. sreenivas\_vishnu@yahoo.com.
\end{enumerate}

\begin{enumerate}
\tightlist
\item
  \textbf{Conflict of Interest/Financial disclosure:} None of the
  authors have any conflict of interest or financial disclosures for the
  purpose of this study.
\item
  \textbf{Ethics:} Ethics approval was taken by the institute ethics
  committee of the All India Institute of Medical Sciences.
\item
  \textbf{Word Count}
\item
  \textbf{Abstract: 247 words}
\item
  \textbf{Main Text: 3480 words}
\item
  \textbf{Number of Tables:} 5
\item
  \textbf{Short running title:} Neurocognition in Survivors of Acute
  lymphoblastic Leukemia from India.
\item
  \textbf{Keywords:} Neurocognition, Acute lymphoblastic leukemia,
  Survivor.
\item
  \textbf{Abbreviations:}
\end{enumerate}\selectlanguage{english}
\begin{longtable}[]{@{}ll@{}}
\toprule
\textbf{Abbreviation} & \textbf{Full Form}\tabularnewline
\midrule
\endhead
ALL & Acute lymphoblastic leukemia\tabularnewline
WISC-\textsuperscript{INDIA} & Wechsler Intelligence Scale for
Children-Fourth Edition\tabularnewline
FSIQ & Full Scale Intelligence Quotient\tabularnewline
CNS & Central nervous system\tabularnewline
\textbf{LMIC} & Low Middle Income Countries\tabularnewline
AIIMS & All India Institute of Medical Sciences\tabularnewline
VCI & Verbal Comprehension Index\tabularnewline
VC & Vocabulary\tabularnewline
CO & Comprehension\tabularnewline
WR & Word reasoning\tabularnewline
IN & Information\tabularnewline
SI & Similarities\tabularnewline
PRI & Perceptual Reasoning Index\tabularnewline
BD & Block designing\tabularnewline
PC & Picture Concepts\tabularnewline
MR & Matrix Reasoning\tabularnewline
PCm & Picture completion\tabularnewline
WMI & Working Memory Index\tabularnewline
DS & Digit Span\tabularnewline
LN & Letter-number sequencing\tabularnewline
AR & Arithmetic\tabularnewline
PSI & Processing Speed Index\tabularnewline
CD & Coding\tabularnewline
SS & Symbol Search\tabularnewline
CA & Cancelling\tabularnewline
SD & Standard Deviation\tabularnewline
IQR & Inter quartile Range\tabularnewline
IV & Intravenous\tabularnewline
IT & Intrathecal\tabularnewline
CRT & Cranial Radiotherapy\tabularnewline
TNF & Tumor Necrosis Factor\tabularnewline
\bottomrule
\end{longtable}

\textbf{ABSTRACT:}

\textbf{BACKGROUND:} Neurocognitive deficits are an important late
effect in survivors of acute lymphoblastic Leukemia(ALL). Data from low
middle income countries is scarce and highly influenced by biological
and cultural variations. Such data would be useful for highlighting the
importance of early intervention in an already disadvantaged population.

\textbf{PROCEDURE:} 70 consecutive survivors of childhood ALL were
evaluated for neurocognitive deficits by the Indian adaptation of
Wechsler Intelligence Scale for Children-Fourth
Edition(WISC-\textsuperscript{INDIA}). Prevalence of neurocognitive
deficits was calculated based on Full Scale Intelligence Quotient(FSIQ)
and scores in discrete domains like Verbal Comprehension, Perceptual
Reasoning, Working Memory and Processing Speed were calculated and
compared to baseline characteristics, chemotherapy and radiation dose
received.

\textbf{RESULTS:} The mean FSIQ was 86.1 \selectlanguage{ngerman}± 20.5, with significant
neurocognitive deficit(FSIQ \textless{}90) being prevalent in 50\%(95\%
CI 38\% to 62\%) of the cohort. The proportion of survivors with
deficits in individual domains of verbal comprehension, perceptual
reasoning, working memory and processing speed were 49\%, 50\%, 47\% and
44\% respectively. The odds of having deficits in neurocognitive
function was higher when a child belonged to lower socioeconomic strata,
had parents with less than primary school education and whose birth
order was higher(All p\textless{}0.05). Age at diagnosis, current age at
assessment, receiving lower or higher dose of radiotherapy, high dose
methotrexate or cytarabine did not have a direct impact on
neurocognitive function.

\textbf{CONCLUSIONS AND RELEVANCE:} The current need is to develop
country specific neurocognition assessment tools to initiate early
screening and develop culturally appropriate preventive and
rehabilitative interventions.



\textbf{INTRODUCTION:}

Acute lymphoblastic leukemia(ALL), being the most prevalent malignancy
of childhood, has seen a barrage of treatment advances in the past few
years\textsuperscript{1}. Better management has lead to improved
survival, which in turn has lead to an increased population of survivors
of ALL. India too has seen a fair share of improvement in survival of
children with ALL, ranging between 41-70\%\textsuperscript{2}. In the
current era , the treatment of ALL is most often done by chemotherapy.
Cranial irradiation is almost obsolete, restricted only to patients
presenting with central nervous system(CNS) positive disease. Targeted
therapy/bone marrow transplantation are considered only in certain high
risk groups. Pediatric oncologists all over the world are approaching a
more holistic approach to cancer care, of which survivorship is an
important component. Late effects are increasingly seen in survivors of
ALL, to the tune of almost 75\%\textsuperscript{3}. Among late effects,
neurocognitive deficits are extremely worrisome and significantly affect
the quality of life of the survivor and the family. Past studies which
have assessed neurocognitive deficits in survivors of acute leukemia
have found its prevalence to be around 38 to 58\%\textsuperscript{4}.
There are significant racial and ethnic variations in the biology of ALL
which may be translated into survivorship, an area that has not been
explored adequately, particularly in Low Middle Income Countries(LMIC).
Hence we conducted a study to evaluate the prevalence and spectrum of
neurocognitive deficits in survivors of childhood ALL, aged 6 to 17
years, who have completed treatment with documented remission of
at-least 2 years and to determine various factors associated with these
deficits.

\textbf{METHODOLOGY}

\textbf{Participants:} ALL survivors attending the Pediatric Cancer
Survivorship Clinic (PCSC) were enrolled after a written informed
consent. The study was performed between July 2016 to November 2017. A
total of 70 survivors of ALL were recruited. The institutional review
board of All India Institute of Medical Sciences(AIIMS), approved the
study protocol. Eligibility criteria included survivors of ALL, aged
6-17 years who had completed treatment and had a documented remission of
atleast 2 years. Exclusion criteria included history of any central
nervous system(CNS) or sensory-motor deficits during treatment,
concurrent neurological or psychiatric disorder not primarily attributed
to ALL or any previous genetic diagnosis with known association with
neurocognitive impairment(eg., Down syndrome).

\textbf{Definitions}

\begin{enumerate}
\tightlist
\item
  \textbf{Treatment completion:} Completion of maintenance phase of
  treatment protocol.
\item
  \textbf{Childhood Cancer Survivor:} One who has completed treatment of
  childhood cancer and is in continued remission for at-least 2 years
  post treatment completion\textsuperscript{5,6}.
\item
  \textbf{Late Effects:} Late effects are defined as any physical or
  psychological outcome that develops or persists after treatment is
  completed\textsuperscript{5,6}.
\item
  \textbf{Neurocognitive Deficits:} Encompasses the group of disorders
  in which the primary clinical deficit is in cognitive function and
  that are acquired rather than developmental\textsuperscript{7}.
\end{enumerate}

\textbf{Sample size:} Based on previous studies\textsuperscript{4}, the
prevalence of neurocognitive deficits in ALL survivors was taken as
58.9\% and the sample size was calculated with a relative precision of
20\% to be 70.

\textbf{Procedures:} Children who met the inclusion criteria, and whose
parents/guardians provided a written informed consent, were included in
the study. Each participant underwent a basic anthropometric evaluation
and medical assessment. Complete demographic details including age, sex,
current address, family type, birth order, parental education levels
were documented. Socioeconomic stratification was done based on the
modified kuppuswamy scale, which is based on education, occupation and
income of the head of the family\textsuperscript{8}. Exposure data,
including chemotherapy used(with cumulative doses), radiation received
and surgical procedures done, was retrieved from the participants
medical records stored in their clinic files. Information was collected
on a detailed proforma.

\textbf{Neurocognitive Evaluation:}

Neurocognitive testing was conducted in dedicated evaluation rooms,
where the testing enviornment was free of distractions and both the
examiner and examinee were comfortable. The Indian adaptation of
Wechsler Intelligence Scale for Children-Fourth
Edition(WISC-IV\textsuperscript{INDIA}) was used for the assessment of
neurocognitive deficits\textsuperscript{9}. This is a valid, reliable
and individually administered comprehensive clinical instrument for
assessing the cognitive ability of children aged between 6 years 0
months to 16 years 11 months and is available commercially.
WISC-IV\textsuperscript{INDIA} assesses four primary domains of
cognition, using 15 subtests, which represent a childs abilities in more
discrete cognitive domains. The scores of the four domains are
integrated to generate the Full Scale Intelligence Quotient(FSIQ), that
represents a child's general intellectual ability.

Before the start of study, training about the
WISC-IV\textsuperscript{INDIA} scale was obtained from the Child
Psychologist, who supervised the assessments and was a co-investigator.
During the study, one fifth of the assessments were randomly
cross-checked by the Psychologist.

As per WISC-IV\textsuperscript{INDIA} the first cognitive domain
assessed is the Verbal Comprehension Index(VCI), using subtests on
Vocabulary(VC), Comprehension(CO), Word reasoning(WR), General
knowledge(Information, IN) and finding similarities(SI). The second
domain assessed is Perceptual Reasoning, which is the ability of a
person to draw upon visual-motor and visual-spatial skills, organize
their thoughts, create solutions, and then test them. The Perceptual
Reasoning Index(PRI) is assessed by Block designing(BD), Picture
conceptualization(Picture concepts, PC), Matrix reasoning(MR) and
Picture completion(PCm). The third domain tested is the Working Memory
Index(WMI). Participants are assessed on their ability to repeat numbers
in order(Digit Span, DS), read a sequence of numbers and
letters(Letter-number sequencing, LN) and mentally solve arithmetic
problems(Arithmetic, AR). The fourth and final domain evaluated is
processing speed which tests the childs ability to focus their
attention, quickly scan and discriminate between objects and put them in
order sequentially. The Processing Speed Index(PSI) is calculated by
drawing symbols in corresponding shapes(Coding, CD), searching for
symbols(Symbol Search, SS) and marking and cancelling targeted
pictures(Cancelling, CA).

There are 10 primary and 5 supplemental subtests. The primary sub tests
are vocabulary, comprehension, finding similarities, block designing,
picture conceptualisation, matrix reasoning, digit span, letter-number
sequencing, coding, and symbol search(10 total). Two subtests were
administered to obtain each of the primary index scores. FSIQ was
derived from 8 of the 10 primary subtests. Acceptable substitutions as
per WISC-IV\textsuperscript{INDIA} manual were taken. Hence, for the
purpose of this study, subtests selected for assessment of FSIQ were
directed at assessing comprehension, similarities, picture completion
and picture conceptualisation, digit span, arithmetic, coding and
cancellation. Each subtest provided a `Raw Score'.~These `Raw Scores'
were converted into a `Scaled Score' using the
WISC-IV\textsuperscript{INDIA} manual based on the exact chronological
age, using the Date of Birth or age in completed years as remembered by
the guardians. Each primary index domain was derived from the sum of
scaled scores.

The FSIQ was obtained from the four primary index scores. The prevalence
of neurocognitive deficits was calculated based on this FSIQ, with
presence of neurocognitive deficits taken at a FSIQ of \textless{}90.
Spectrum of deficits was analysed by calculating the prevalence of
deficits in each of the 4 primary index scores. Any score less than 90
was considered as a deficit in that particular domain. A structured
record form was used to document all assessment details, scores and
calculations.

\textbf{Statistical Analysis:} The data was analysed using with STATA
14.2 software. Categorical data was tested by the Chi-square or Fischer
extract test and presented as percentage or proportion. Continuous data,
which was normally distributed, was presented as Mean ± Standard
Deviation(Mean ± SD) and the data which is not normally distributed is
presented as Median with corresponding Inter-Quartile Range(Median +
IQR). The prevalence of neurocognitive deficits in the sample population
was calculated in percentage, including complete and individual demain
deficits. The various factors associated with neurocognitive deficits in
sample population was also assessed using multiple logistic regression
analysis. Odds ratio was calculated along with 95\% confidence interval.
In all analysis, p value \textless{}0.05 was considered to represent a
statistically significant difference.

\textbf{RESULTS}

\textbf{Baseline characteristics:}

Baseline characteristics are provided in \textbf{Table 1} . Treatment
was instituted as per chemotherapy protocols of the intitute at that
period of time which were differed among patients. Details of relevant
cumulative drugs are provided. Radiotherapy was received by all patients
as per protocol(1260cGy for prophylaxis and 1800cGy to treat CNS
positive leukemia). As per treatment protocol at the time, our cohort
received either Protocol A or B. Protocol B included high dose
methothrexate, triple IT and a higher dose of dexamethasone and
cyatarabine as compared to protocol A. Our cohort averaged a total of
27.1 months of delay in schooling.

\textbf{Neurocognitive outcomes (Table 2):}

The primary outcome assessed in this study was the full scale
intelligence quotient (FSIQ). The mean FSIQ of the entire sample
population was 86.1 ± 20.5. The prevalence(95\% confidence interval) of
significant neurocognitive deficits(FSIQ \textless{}90) in the sample
population was 50\%(38\% - 62\%), with 18 children having extremely low
FSIQ(25.7\%), 7 with borderline FSIQ (10.0\%) and 10 with low average
FSIQ(14.3\%).

\textbf{Individual domains (Table 3):}

Using the WSIC-IV\textsuperscript{INDIA}, various domains of
neurocognition was assessed. The first domain is verbal comprehension,
assessed by the Verbal Comprehension Index. The mean VCI of the entire
sample population was 88.4(SD 21.6), with 34(49\%) children showing a
significant deficit in this domain(VCI score \textless{} 90).

The second domain was perceptual reasoning, whach was tested by the
Perceptual Reasoning Index and included assessment of block designing,
picture conceptualization, matrix reasoning and picture completion
abilities. The PRI was 89.0(SD 18.0) with 35(50\%) of the population
having a score of \textless{}90.

The working memory of the entire sample population was the third domain
assessed. The mean WMI calculated was 87.5(SD 21.0) and 33(47\%)
children were found to have a significant deficit of WMI(\textless{}
90).

The fourth and final domain evaluated was the processing speed ability
of an individual by the processing speed index. The mean PSI of the
entire sample population was 90.3(SD 19.0) with 3(44\%) children having
clinically significant neurocognitive deficit.

\textbf{Patient related risk factors associated with poor neurocognitive
domains (Table 4):}

Univariate analysis with multivariate logistic regression was used to
assess various risk factors associated with significant neurocognitive
deficits (FSIQ\textless{}90). The odds of having deficits in
neurocognitive function was 5.7 times when a child belonged to lower
socioeconomic strata as compared to a child belonging to middle
socioeconomic strata (p value=0.004). Parental education had a
significant association with adverse neurocognitive deficit with odds
being higher when parents were only educated till primary school(4.3 to
4.6 times higher when the father or mother was educated up to primary
school respectively). Children whose birth order was 3 or more had a
higher probability of having deficits in neurocognitive function(20.1
times higher, p value=0.005). Other factors including gender, age at
assessment, age at diagnosis/initiation of treatment and family type did
not show any significant association with poorer neurocognitive scores.

\textbf{Disease and treatment related risk factors associated with poor
neurocognitive domains (Table 4):}

Age at diagnosis/initiation of therapy did not affect the neurocognitive
scores. The entire cohort of patients received either prophylactic or
therapeutic cranial radiotherapy(RT). The presence of CNS disease would
entail receiving higher dose of RT to the neuralaxis. Receiving higher
doses of RT to the neuralaxis was also not associated with poorer FSIQs.
Chemotherapy protocol received did not have a directder age at
assessment was associated impact on neurocognitive function. Giving
higher doses of intravenous methotrexate or cytarabine or using triple
IT over IT methotrexate was not associated with increased neurocognitive
deficits(OR: 1.0 , 95\% CI 0.3-3.5, p 1.000).

\textbf{Individual cognitive domains in relation to patient and
treatment related risk factors (Table 5):}

Older age at diagnosis was associated with significantly improved
working memory scores. Median age at diagnosis or age at assessment was
similar in all other major domains of neurocognition. These scores were
also no different between the two genders, type of radiation received or
type of chemotherapy used.



\textbf{DISCUSSION}

One of the main challenges after curative treatment of childhood cancer
is maintaining an effective follow up to assess various health related
complications. There are a wide range of late effects as a result of
cancer and its therapeutic exposure. Studies have shown that the
cumulative number of health conditions in survivors of ALL are actually
twice that identified among matched controls, particulary
cardiovascular, endocrine, reproductive and neurological
sequelae\textsuperscript{10}. At a mean duration of around 5 years from
diagnosis, 50\% of our cohort of ALL survivors showed significant
disturbance in neurocognitive function. Around 75\% of our cohort showed
a deficit in atleast one domain of neurocognition, which includes verbal
comprehension, working memory, processing speed and perceptual
reasoning. This is comparable to a large series of adult survivors of
ALL, where neurocognitive impairment ranged between 28.6\% for
self-reported behavior problems to 58.9\% for direct assessment of
executive function\textsuperscript{4}. The mean FSIQ of ALL survivors
from developed countries are almost 20-30 points higher than in our
cohort\textsuperscript{11,12}. This could be due to regional variation
in IQ and socioeconomic status between the two cohorts. However it also
signifies the greater need to implement more stringent long term follow
up guidelines in LMICs as the baseline prevalence of neurocognitive
impairment is high.

Data on neurocognitive outcome in survivors of ALL in LMICs is scarce.
According to a review of neurocognitive impairment in Asian Cancer
survivors, mild-to-moderate impairment was reported in 10.0--42.8\% of
survivors\textsuperscript{13}. A large series of cancer survivors from
India, showed scholastic problems and psychosocial problems in around
43\% and 57\% of the cohort, respectively\textsuperscript{14}. Racial,
regional and ethnic variations of cancer and its treatment are known,
which increases the burden of chronic health condition in this growing
survivor population in LMICs. Hence, the importance of country specific
databases of childhood cancer survivors.

As early as 1988, neurobehavioural effect of CRT in survivors of ALL
have been demonstrated\textsuperscript{15}. These late effects include
deficits in attention, memory, processing speed, and visual spatial
skills\textsuperscript{16}. Demyelination with loss of white matter,
microvascular damage, loss of neuronal precursors in hippocampus, basal
ganglia and thalamus are all proposed mechanisms for long term radiation
induced cognitive decline\textsuperscript{17}. This neurocognitive
morbidity in survivors of childhood ALL has led to the phasing out of
radiation, almost completely from the management of
ALL\textsuperscript{18,19}. Acute changes in the brain occurring during
chemotherapy are also associated with long term neuro behavioural
problems\textsuperscript{20}. Despite elimination of CRT, modern
treatment protocols including high dose methotrexate and IT
methotrexate, have been implicated in long term problems in memory,
executive function, attention and processing
speed\textsuperscript{4,21,22}. Methotrexate depletes the folate pool
which in turn depletes the availability of methyl-groups and produces an
excess of homocysteine and alternative one-carbon sources such as
choline and betaine. This leads to an impairment in myelin formation and
stabilisation and is a likely explanation for methotrexate induced long
lasting neurodevelopmental impairment\textsuperscript{23}. Higher plasma
methotrexate levels have been shown to be associated with poorer
executive function scores\textsuperscript{4}. In one study methotrexate
decreased the processing speed by 3\% for each 1g/m\textsuperscript{2}of
methotrexate\textsuperscript{4}. A study comparing IT methotrexate with
triple IT revealed minor reduction in processing speed in survivors of
ALL. CRT, high dose methotrexate and IT therapy have a neurotoxic effect
in the early course of therapy. As time passes neurocognitive problems
are a result of other therapies like glucocorticoids. The cerebellum and
hippocampi have higher number of glucocorticoid receptors and are more
affected by exposure to prolonged and high doses of
steroids\textsuperscript{24}. Comparisons between different
glucocorticoids have also been made. Neurocognitive outcome measures
evaluated in survivors receiving dexamethasone or prednisolone during
induction of ALL, found no difference in outcome measures in either
group\textsuperscript{25}. Even though almost half of our cohort had
neurocognitive dysfunction, the scores were not different in groups of
patients receiveing higher dose of CRT compared to lower doses(24Gy vs
18Gy). Higher dose of methotrexate or use of IT methotrexate so did not
appear to have adverse effect on neurocognition in our group of
survivors. Other factors that can be evaluated to assess the risk of
neurotoxicity include markers of oxidative stress\textsuperscript{26},
cytokines like tumor necrosis factor(TNF) alpha and
interleukins\textsuperscript{27} and cerebrospinal fluid
biomarkers\textsuperscript{28}.

Neurocognitive dysfunction is seen to be more significant as age
increases\textsuperscript{29}. Attention problems detected at the end of
therapy in survivors of ALL predicted decreased academic performance 2
years later, especially in females and children who had a younger age at
diagnosis\textsuperscript{30}. It is also believed that patients
diagnosed at a younger age and those who received CRT, perform poorly in
neurocognitive domains\textsuperscript{13,16}. A younger age at
diagnosis correlated with poor working memory scores in our cohort.
Other domains were not affected by either the age at diagnosis or
assessment. Nevertheless, assessment of neurocognition in survivors of
ALL should start at a younger age, especially in children in LMICs,
where focus is more on survival than survivorship, to allow them to
reach their full potential at school and in the workplace.

Additional factors which put a survivor at increased risk of
neurocognitive impairment, like polymorphisms in genes related to
neurodevelopment, genes affecting the folate pathway and genes that
regulate oxidative stress, have been studied\textsuperscript{31}. This
can not only help us in stratifying patients according to their genetic
risk but also help in tailoring treatment and prophylaxis early in
development\textsuperscript{32}. Since regional variations affect the
genetic makeup of an individual, country specific multicentre
collaborative studies are in much need.

There is limited research examining how a childs neurocognitive function
following treatment for cancer is associated with parenting factors. A
recent study reported that parents respond to child executive function
difficulties with greater over protection. Greater years of maternal
education were related to less parental perceptions of child
vulnerability and less over protection\textsuperscript{33}. A univariate
analysis in our cohort, showed a significantly lower Intelligence
quotient(IQ) in survivors whos' parents had fewer years of education.
Other factors like lower socioeconomic status and increased birth order
are also associated with lower IQ scores. These are predictable and
understandable findings and may also be seen in children who are not
cancer survivors. However, since other factors including radiation dose,
intensity of chemotherapy or age at primary diagnosis did not alter
outcome, focus of neurocognitive behavioural assessment and intervention
should be more focussed towards this more vulnerable group of children
and adolescents to mitigate the impact of therapy on neurocognitive
outcomes.

Poor neurocognition in ALL survivors, has been associated with a marked
decrease in quality of life due to increased chronic health
morbidities\textsuperscript{34}. Survivors of ALL have been believed to
perform poorly in school because of probable dysfunction in executive
function abilities\textsuperscript{(4(p20)}. Compared to their siblings,
they have greater degrees of inattention-hyperactivity, anxiety,
depression, social withdrawal and learning problems. Adolescent
survivors with neurocognitive impairment are also less likely to
graduate from college than survivors without any
impairment\textsuperscript{30}. The St Judes Lifetime Cohort study
concluded that though survivors of ALL had significant neurocognitive
impairment, overall their educational attainment and employment status
was similar to controls\textsuperscript{4}. Delay in schooling is a
major concern in survivors of ALL from India. Our cohort showed an
average of 27 months of delay in schooling despite our best efforts.
LMICs, which have their own cohort of young survivors, with poorer
overall exposure to basic education, must focus on routine longitudinal
screening in childhood survivors of ALL, optimizing their educational,
vocational, and social outcomes based on local, regional and cultural
practices.

Following a good assessment, survivors of ALL with neurocognitive
impairment, should should be taught deficit specific compensatory
interventions. This may be a computerised, home, school or even
community based training\textsuperscript{31}. Pharmacological agents
have also been studied. Methylphenidate resulted in a statistically
significant improvement in measures related to
attention\textsuperscript{35}. Future research should focus on
interventions to improve neurocognition in ALL survivors.

Several limitations should be considered in interpretation of these
results. Firstly, this was a cross sectional study with a small sample
size restricted by geographical coverage. Secondly baseline
neurocognitive functions of these ALL survivors were not known and there
was no healthy control group for comparison. Assessment at time of
initiation of treatment may have yieldied falsely low scores associated
with anxiety and stress at diagnosis. Thirdly, due to a lack of region
specific assessment tools for neurocognitive function, we had to use
region specific adaptations of the assessment tool which allowed certain
substitutions. Limitations notwithstanding, comparisons were made across
treatment groups and patients with or without significant neurocognitive
impairment. In addition, the primary focus of this study was to assess
the neurocognitive impairment in a group of survivors from a LMIC where
baseline educational and vocational opportuinites are challenging even
for children without cancer. To the best of our knowledge this was the
first study in India, a LMIC, in which WISC-IV scale was used for the
assessment of neurocognitive functions in the survivors of childhood
ALL. We looked extensively into various factors associated with
neurocognitive deficits including host, disease and treatment related
factors.

In conclusion, data on neurocognitive outcomes in survivors of ALL are
extremely scarce, this being particularly true for our country. Ethnic,
geographic and genetic variations predispose survivors differently to
adverse chronic neurological toxicities. This can explain the difference
in prevalence, severity, and presentation of neurocognitive impairment
in survivors of ALL in LMICs. More data from LMICs are needed to assess
the time to initiate screening and ways to identify potentially
remediable risk factors which in turn will enable us to develop
culturally appropriate preventive and rehabilitative interventions.

\subsection*{Funding Support:}

{\label{funding-support}}

\subsection*{No financial disclosures.}

{\label{no-financial-disclosures.}}

\subsection*{Conflict of Interest
Disclosures:}

{\label{conflict-of-interest-disclosures}}

No conflict of interest disclosures.

\subsection*{Author Contributions:}

{\label{author-contributions}}

\textbf{Vishwa CR:}~Data collection and analysis, writing-original
draft.~\textbf{Gargi Das:} Statistical analysis and writing the final
draft.~\textbf{Rachna Seth:}~Planning the study, supervision, writing
the final draft and data analysis.~\textbf{Savita Sapra:} Planning the
study, neurocognitive assessment on children, data analysis, editing
final manuscript. \textbf{Prasanth Sri:} Data analysis and editing the
final draft. \textbf{Jagdish Prasad Meena, Aditya Kumar
Gupta:}Supervision, editing the final draft. \textbf{Vishnu Sreenivas:}
Data analysis.



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\textbf{TABLES}

\textbf{TABLE 1 Baseline characteristics of the population}\selectlanguage{english}
\begin{longtable}[]{@{}ll@{}}
\toprule
\textbf{Characteristic} & \textbf{Result (n=70)}\tabularnewline
\midrule
\endhead
\textbf{Patient related characteristics} & \textbf{Patient related
characteristics}\tabularnewline
\selectlanguage{ngerman}\textbf{Mean Age (± SD)} & 10.5 (\selectlanguage{ngerman}± 3.2) years\tabularnewline
\textbf{Mean duration between diagnosis and enrolment (± SD)} & 5.0 (\selectlanguage{ngerman}±
2.8) years\tabularnewline
\textbf{Age distribution} 6-9 years 10-13 years 14-17 years & \textbf{N
(\%)} 34 (48) 18 (26) 18 (26)\tabularnewline
\textbf{Gender} Male Female & 54 (77) 16 (23)\tabularnewline
\textbf{Socioeconomic strata} Upper Strata Middle Strata Lower Strata &
14 (20) 32 (45) 24 (35)\tabularnewline
\textbf{Parental education} \textless{}Primary school education
\textgreater{}Primary school education & 36 (25) 104 (75)\tabularnewline
\textbf{Birth order} \textless{}=2 \textgreater{}2 & 56 (80) 14
(20)\tabularnewline
\textbf{Family Type} Nuclear Multi Generational & 30 (43) 40
(57)\tabularnewline
\textbf{Disease and Treatment Related} & \textbf{Disease and Treatment
Related}\tabularnewline
\textbf{CNS disease at diagnosis} Positive Negative & 8 (11) 62
(89)\tabularnewline
\textbf{Radiation received} Therapeutic \textbf{(}1800 cGy) Prophylactic
(1260 cGy) & 8 (11) 62 (89)\tabularnewline
\textbf{Chemotherapy what is protocol A and B} \textbf{Protocol A:} IV
Methotrexate at 0 mg/m\textsuperscript{2} Intrathecal (IT) methotrexate
only Prednisolone 4040 mg/m\textsuperscript{2} Dexamethasone 40
mg/m\textsuperscript{2} IV Cytarabine 16400 mg/m\textsuperscript{2}
\textbf{Protocol B:} IV methotrexate at 5800 mg/m\textsuperscript{2}
Triple IT Prednisolone 2880 mg/m\textsuperscript{2} Dexamethasone 670
mg/m\textsuperscript{2} IV Cytarabine 30400 mg/m\textsuperscript{2} & 58
(83) 12 (17)\tabularnewline
\bottomrule
\end{longtable}

\textbf{TABLE 2 FSIQ distribution in the sample population}\selectlanguage{english}
\begin{longtable}[]{@{}lll@{}}
\toprule
\textbf{FSIQ} & \textbf{Class} & \textbf{Number (\%)}\tabularnewline
\midrule
\endhead
\textless{}70 & Extremely Low & 18 (26)\tabularnewline
70-79 & Borderline & 7 (10)\tabularnewline
80-89 & Low Average & 10 (14)\tabularnewline
90-109 & Average & 26 (37)\tabularnewline
110-119 & High Average & 5 (7)\tabularnewline
120-129 & Superior & 3 (4)\tabularnewline
\textgreater{}129 & Very Superior & 1 (2)\tabularnewline
\bottomrule
\end{longtable}

\textbf{TABLE 3 Prevalence of significant deficit in various individual
domains}\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
\begin{minipage}[b]{0.22\columnwidth}\raggedright\strut
\textbf{Primary Index score}\strut
\end{minipage} & \begin{minipage}[b]{0.22\columnwidth}\raggedright\strut
\textbf{Number of children with significant deficit (Prevalence in
\%)}\strut
\end{minipage} & \begin{minipage}[b]{0.22\columnwidth}\raggedright\strut
\textbf{95\% CI}\strut
\end{minipage} & \begin{minipage}[b]{0.22\columnwidth}\raggedright\strut
\textbf{Mean +/- SD}\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
\textbf{Verbal comprehension} VCI\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
34 (49)\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
37\%-60\%\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
88.4 +/- 21.6\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
\textbf{Perceptual Reasoning} PRI\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
35 (50)\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
38\%-62\%\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
89.0 +/- 18.0\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
\textbf{Working Memory} WMI\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
33 (47)\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
35\%-59\%\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
87.5 +/- 21.0\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
\textbf{Processing speed} PSI\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
31 (44)\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
32\%-56\%\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
90.3 +/- 19.0\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}



\textbf{TABLE 4: Risk factors associated with significant neurocognitive
deficit}\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
\begin{minipage}[b]{0.17\columnwidth}\raggedright\strut
\textbf{Character}\strut
\end{minipage} & \begin{minipage}[b]{0.17\columnwidth}\raggedright\strut
\textbf{FSIQ}\strut
\end{minipage} & \begin{minipage}[b]{0.17\columnwidth}\raggedright\strut
\textbf{FSIQ}\strut
\end{minipage} & \begin{minipage}[b]{0.17\columnwidth}\raggedright\strut
\textbf{FSIQ}\strut
\end{minipage} & \begin{minipage}[b]{0.17\columnwidth}\raggedright\strut
\textbf{FSIQ}\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\textbf{Normal(n=35)}\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\textbf{Deficiency(n=35)}\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\textbf{Odds Ratio (95\% CI)}\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\textbf{p value}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\textbf{Gender} Male, N (\%) Female, N (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
25 (71) 10 (29)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
29 (83) 6 (17)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
1.9 (0.6-6.1)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
0.259\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\textbf{Socioeconomic status} Upper Class, N (\%) Middle Class, N (\%)
Lower Class, N (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
8 (23) 21 (60) 6 (17)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
6 (17) 11 (31) 18 (52)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
5.7(1.8-18.6)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
0.004\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\textbf{Maternal education} \textless{}=Primary, N (\%)
\textgreater{}Primary, N (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
6 (17) 29 (83)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
17 (49) 18 (51)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
4.6(1.5-13.7)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
0.007\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\textbf{Paternal education} \textless{}=Primary, N (\%)
\textgreater{}Primary, N (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
3 (9) 32 (91)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
10 (28) 25 (72)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
4.3(1.1-17.2)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
0.041\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\textbf{Birth Order} 1-2, N (\%) 3 or more, N (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
34 (97) 1 (3)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
22 (63) 13 (37)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
20.1(2.5-164.6)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
0.005\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\textbf{Family type} Multi Generational. N (\%) Nuclear, N (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
19 (54) 16 (46)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
21 (60) 14 (40)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
1.3 (0.5-3.3)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
0.629\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\textbf{Age at assessment} \textless{}10 years, N (\%) \textgreater{}=10
years, N (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
18 (51) 17 (49)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
16 (46) 19 (54)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
1.3 (0.49-3.22)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
0.632\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\textbf{Age at diagnosis} \textless{}4 years, N (\%) \textgreater{}=4
years, N (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
13 (37) 22 (63)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
12 (34) 23 (66)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
0.8 (0.33-2.34)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
0.803\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\textbf{Chemotherapy} Protocol A, N (\%) Protocol B, N (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
29 (83) 6 (17)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
29 (83) 6 (17)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
1.0 (0.3-3.5)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
1.000\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\textbf{Radiotherapy} 1260 cGy, N (\%) 1800 cGy, N (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
32 (91) 3 (9)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
30 (89) 5 (11)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
1.8(0.4-8.1)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
0.457\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}\selectlanguage{english}
\begin{longtable}[]{@{}llllllllllllll@{}}
\toprule
\textbf{Risk Factor} & \textbf{Risk Factor} & \textbf{VCI} &
\textbf{VCI} & \textbf{VCI} & \textbf{PSI} & \textbf{PSI} & \textbf{PSI}
& \textbf{WMI} & \textbf{WMI} & \textbf{WMI} & \textbf{PRI} &
\textbf{PRI} & \textbf{PRI}\tabularnewline
\midrule
\endhead
& & \textbf{\textless{}90} & \textbf{\textgreater{}=90} & \textbf{P} &
\textbf{\textless{}90} & \textbf{\textgreater{}=90} & \textbf{P} &
\textbf{\textless{}90} & \textbf{\textgreater{}=90} & \textbf{P} &
\textbf{\textless{}90} & \textbf{\textgreater{}=90} &
\textbf{P}\tabularnewline
Age in months at Diagnosis & Median age (IQR) & 55 (23-155) & 62
(16-137) & 0.18 & 68 (29-155) & 58 (16-131) & 0.39 & 53 (16-155) & 66
(20-137) & 0.03 & 72 (23-155) & 58 (16-137) & 0.16\tabularnewline
Age in months at assessment & Median age (IQR) & 122 (72-203) & 115
(63-196) & 0.19 & 120 (72-196) & 121 (63-203) & 0.05 & 121 (63-203) &
117 (76-196) & 0.16 & 121 (72-203) & 115 (63-196) & 0.19\tabularnewline
Gender & Male, N (\%) & 26 (76) & 28 (78) & 1.00 & 26 (84) & 28 (72) &
0.26 & 28 (85) & 26 (70) & 0.167 & 28 (80) & 26 (75) &
0.77\tabularnewline
& Female, N (\%) & 8 (24) & 8 (22) & & 5 (16) & 11 (28) & & 5 (15) & 11
(29) & & 7 (20) & 9 (25) &\tabularnewline
Radiotherapy & 1280 cGy, N (\%) & 29 (85) & 33 (92) & 0.47 & 26 (84) &
36 (93) & 0.45 & 28 (85) & 34 (92) & 0.46 & 30 (85) & 32 (91) &
0.71\tabularnewline
& 1800 cGy, N (\%) & 5 (15) & 3 (8) & & 5 (16) & 3 (7) & & 5 (15) & 3
(8) & & 5 (15) & 3 (9) &\tabularnewline
Chemotherapy & Protocol A, N (\%) & 29 (85) & 29 (80) & 0.75 & 25 (81) &
33 (85) & 0.75 & 26 (79) & 32 (86) & 0.53 & 27 (77) & 31 (89) &
0.34\tabularnewline
& Protocol B, N (\%) & 5 (15) & 7 (20) & & 6 (19) & 6 (15) & & 7 (21) &
5 (14) & & 8 (23) & 4 (11) &\tabularnewline
\bottomrule
\end{longtable}

\textbf{TABLE 5 Risk factors associated with individual deficits in the
neurocognitive domain}

\textbf{Hosted file}

\verb`Table 1 Baseline characteristics of the population.docx`  available at \url{https://authorea.com/users/416997/articles/524259-title-page-neurocogntive-outcomes-in-survivors-of-childhood-acute-lymphoblastic-leukemia-experience-from-a-teritary-care-centre-in-india}

\textbf{Hosted file}

\verb`Table 2 FSIQ distribution in the sample population.docx`  available at \url{https://authorea.com/users/416997/articles/524259-title-page-neurocogntive-outcomes-in-survivors-of-childhood-acute-lymphoblastic-leukemia-experience-from-a-teritary-care-centre-in-india}

\textbf{Hosted file}

\verb`Table 3 Prevalence of significant deficit in various individual domains.docx`  available at \url{https://authorea.com/users/416997/articles/524259-title-page-neurocogntive-outcomes-in-survivors-of-childhood-acute-lymphoblastic-leukemia-experience-from-a-teritary-care-centre-in-india}

\textbf{Hosted file}

\verb`Table 4 Risk factors associated with significant neurocognitive deficit.docx`  available at \url{https://authorea.com/users/416997/articles/524259-title-page-neurocogntive-outcomes-in-survivors-of-childhood-acute-lymphoblastic-leukemia-experience-from-a-teritary-care-centre-in-india}

\textbf{Hosted file}

\verb`Table 5 Table 5- Risk factors associated with individual deficits in the neurocognitive domain .docx`  available at \url{https://authorea.com/users/416997/articles/524259-title-page-neurocogntive-outcomes-in-survivors-of-childhood-acute-lymphoblastic-leukemia-experience-from-a-teritary-care-centre-in-india}

\selectlanguage{english}
\FloatBarrier
\end{document}

