FP800 : Low Body Mass Index in pediatric orbital and ocular malignancies: A key prognostic indicator

Dr.Jayanta Kumar Das

Abstract:

Body mass index (BMI) is an important tool to assess health status of an individual. The aim of this study is to evaluate the role of BMI as a prognostic factor for ocular and orbital malignancies in pediatric patients. A  prospective case control study  was conducted from Jan 2007 to Dec 2017,   137 of ocular and 33 of orbital malignancies and equal number of age and sex matched  children attending pediatric eye OPD for refractive error were included as controls.

Recurrence of the disease and death of the patient were calculated and compared with the published data of western population. Mean BMI of ocular tumor and control group was 21.45(±2.6) and 22.93(±2.09) respectively with p value of 0.036 and for orbital tumor was 21.48(±2.25) and 22.78(±2.70) respectively and with p value of 0.001, which is significant at < 0.05, done by independent t-test. Low BMI at the time of first diagnosis is a significant factor for high rate of treatment failure, in terms of recurrence and mortality.

Introduction:

The body mass index (BMI), or Quetelet index, is a statistical measurement which compares a person’s weight and height. Though it does not actually measure the percentage of body fat, it is a useful tool to estimate a healthy person. BMI is defined as the individual’s body weight divided by the square of height. BMI=weight (kg)/ height² (m²). Due to its ease of measurement and calculation, it is the most widely used diagnostic tool to identify weight problem within a population.

A high body mass index (BMI) is thought to be associated with various health conditions such as cardiovascular disease, hypertension and type II diabetes mellitus, the biological mechanisms of which have been well documented (Inoue M et al. 2004) BMI has also been linked to cancer. According to recent expert consultation reports by World Health Organization (WHO)/Food and Agriculture Organization (FAO), a high BMI and obesity have been categorized as ‘‘convincing’’ risk factors for cancer of various sites, including the esophagus, colo-rectum,

breast in postmenopausal women, endometrium and kidney (Inoue M  et al. 2004).  The incidence of obesity is increasing in the developed world. Obesity is associated with an increased risk of malignancy, contributing to 14%–20% of cancer-related mortality (Calle EE et al 2003) but an association between obesity and cancer survival is less clear. Although obese women are more likely to develop endometrial cancer, there is evidence that they have improved survival (Temkin SM et al. 2007). On the other hand , in case of ovarian cancer, one study identified increased body mass index (BMI) as an independent negative prognostic factor for disease-free survival (DFS) and overall survival (OS) (Pavelka JC,et al. 2006). 

The impact of BMI on total cancer has been investigated, mainly in Western developed countries (Inoue M et al. 2004). Most of these reports have targeted cancer mortality, and they consistently observed a positive link between cancer mortality and obesity (Inoue M et al. 2004). On the other hand children are particularly vulnerable to malnutrition because they have decreased calorie stores and need extra calories for growth and development (Han-Markey et al. 2000). The literature suggests that anything between 1-46% of pediatric oncology patients could be experiencing malnutrition (Pietsch and Ford 2000). Malnutrition is a problem for all oncology patients, childhood malignancy is no exception.

Material and Methods:

A case control study was carried out in eastern part of India involving four tertiary care hospitals over the period of four years in between January 2007- December 2017. In study group total of 170 pediatric ocular and orbital malignancy were included, 137 were ocular and 33 patients of orbital. Controls were frequency matched with the cases on age, sex, geographical locality and demographic profile. In orbital malignancy, 12 cases of Rhabdomyosarcoma, 12 patients were orbital manifestation of Acute Myeloid leukemia, four cases of neuroblastoma three patients of malignant histiocytosis and two cases of non-hodgkins lymphoma.

The demographical variables recorded were the medical record number, hospital-indoor registration number, date of first reporting/admission, name, age, sex, address, ethnicity, socioeconomic condition. All the cases were subjected to clinical history taking including history of family, consanguinity, exposure to any toxic substances (eg, chemicals) and radiation hazard were thoroughly investigated, apart from standard clinical examination and investigation. Cases and control group enrolment criteria:

Enrolment criteria for study group:

The cases were identified directly by the investigators who reported four tertiary care hospital in the above mention period. The all the cases of orbital malignancy were to have been newly diagnosed in between January 2007 to December 2017. Patients were also required to be less than 18 years of age and residing in the specific geographical region for more than six months, before diagnosed with the disease were considered as residents for the demographical data.

Enrolment for control group: Thirty three children of age and sex matched included for control with the same geographical locality and demographic profile, fulfilling similar criteria with cases including same economic background.   BMI calculation:

BMI was calculated from the height and weight recorded at first treatment using the formula: weight (kg)/height² (m²). Patients were assigned to one of three categories: underweight (BMI < 18.5), ideal weight (BMI 18.5–24.9), overweight (BMI 25or above). Survival was compared between these three groups using the log-rank test.

Statistical application:  In our study, the BMI was used as a mean of correlation between control and disease group (ocular and orbital malignancy cases). Independent t –test was done separately for both ocular and orbital group as well as in combine also.

Observation:

In the study group 137 number of intra-ocular malignancy were included. Most of them are retinoblastoma, which is a common childhood malignant tumor. 10 cases of intra ocular manifestation of leukemia and rest two, Malignant melanoma of the cilliary body and meduloepithelioma.

In orbital group, a total of 33 patients of childhood orbital malignancy were included. 12 cases of Rhabdomyosarcoma, 12 patients had Acute Myeloid leukemia, four cases of neuroblastoma , three cases of orbital Histiocytosis and two patients of non-hodgkins lymphoma at the time of presentation. Equal numbers of children and family were taken in control group. Nineteen cases (57.6%)were male and fourteen cases(42.4%) were female in both study and control group.

Fig 1. Bar diagram representing BMI of cases and control of ocular malignancies. Values in the vertical axis are the mean of the each group +_SD. The mean of case and control group was 21.45 (+_ SD 2.6) and 22.93(+_2.09) respectively. By independent t-test p  value was found 0.036 , which is significant  at < 0.05 level.

Fig 2. Bar diagram representing BMI of cases and control of orbital malignancies. Values in the vertical axis are the mean of the each group +_SD. The mean of case and control group was 21.48 (+_ SD 2.25) and 22.78(+_2.70) respectively. By independent  t-test p  value was found 0.001 , which is significant  at < 0.05 level.

Fig 3. Bar diagram representing BMI of cases and control of combination of total orbital and ocular malignancies Values in the vertical axis are the mean of the each group ±SD. The mean of case and control group was 21.46 (±SD 2.60) and 22.91(±2.20) respectively. By independent t-test p value was found 0.001, which is significant at < 0.05 level.

The mean ages of study and control groups are 6.24 and 6.03 years respectively. All patients of ocular and orbital malignant tumor were recruited from four referral centers of our region in between January 2005 to December 2008. Parents of patients gave informed consent to participate and the trial had ethics committee approval of the respective institute.

Discussion:

The side effects of the cancer treatment can also affect dietary input by triggering nausea, vomiting and mucositis. The cancer itself can cause a severe form of malnutrition known as Cachexia. This is a progressive muscle wasting caused by a failure to meet protein or calorie requirements (Cunningham and Bell, 2000). Chemicals released by the tumor and the patient’s body cause them to lose both fat and lean body mass, namely skeletal muscle. Cachexia is linked to a decrease in response to treatment and death (Davis et al. 2002, Conner J M et al 2016).

Drug elimination may also differ between ideal weight and obese patients. A recent study in patients with solid tumours reported that, for every increase in BSA of 0.2 m², there is a 9% increase in drug elimination (Joerger M et al. 2006). This finding further supports the argument that obese patients should receive chemotherapy based on actual body weight (Barr R D 2015).

BMI as an etiology of any malignancy has never been explored, though it is co-related as a risk factor in many malignancies. A study on the status of BMI at the time of diagnosis of malignancy before starting any kind of therapy may shed some light on this aspect. It has been reported in literature that low BMI is related to lung cancer amongst the cigarette smokers.

Low BMI at the time of diagnosis has been found in many types of malignancy. And as the developing countries have a high incidence and aggressive form of malignancies, therefore low BMI may be taken as a contributing factor along with his prognostic impact. Till now none of the study has estimated the role of BMI in pediatric cancer. Some studies addressing the role of BMI in adult population in western literature highlighting BMI mainly as a prognostic factor. As per literature review, this is the first prospective case control study in this subject.

Though some argue that the error in BMI is insignificant and so pervasive that is not generally useful in evaluation of health 14. Moreover an analysis based on data gathered in USA suggested an exponent of 2.6 would yield the best fit for children aged 2 to 19 years old.13 (BMI NOTE). Considering the pediatric age group population of our study, the BMI was tried to use as an epidemiological tool in our study. BMI of mean 22.91 (±2.20) was found in the control group whereas in the case group 21.46 (±2.60),  BMI lower than control group.

Thus Low BMI at the time of detection before starting any intervention was commonly seen in patient suffering orbital malignancy. However what needs to be evaluated is the role of prolonged low BMI in the causation of the disease condition.  Lack of serial BMI data prior to the detection of the disease condition hampers our analysis of its relation with the disease process as it has been found to be co-related with the disease. 

Futuristic Approach

The present study is a series of 170 cases of different type of malignancies along with various affected sites.  Co-relating BMI as an etiology in such a varied group has limitations. A study on a larger scale, concentrating on one particular malignancy and site would provide more definitive information. Assessment at various stages of the disease condition would also provide a broader picture for analyzing the role of BMI. Information on concurrent medication and its effect on the BMI would help analyze and narrow down to the real factor affecting the BMI , as it has been noted that systemic steroids taken during a disease process have increased bodyweight and inadvertently influenced BMI

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