Unmasking the Hidden Shifts: Why Your BMI Doesn’t Tell the Whole Story in Pediatric Cancer Treatment
Disclaimer: This content was generated by NotebookLM and has been reviewed for accuracy by Dr. Tram.
Imagine a young person battling lymphoma, undergoing chemotherapy – a tough journey in itself. We often track their progress using simple measures like weight and Body Mass Index (BMI). But what if these traditional tools are missing a critical part of the picture? A groundbreaking study published in European Radiology by Tram et al. (2022) reveals that for pediatric, adolescent, and young adult (AYA) lymphoma patients, BMI is often a misleading measure of chemotherapy’s impact on their body composition, while routine CT scans can uncover vital, hidden changes.
The Limitations of BMI: More Than Just a Number
For years, healthcare professionals have relied on anthropometric measures like BMI, skinfold thickness, and waist circumference to assess body composition (BC). These methods are easy to use and readily available. Chemotherapy doses are even often based on measures like body surface area and BMI. However, the Tram et al. study, along with previous research, highlights a major flaw: these measures don’t differentiate between lean mass (like muscle) and fat mass.
Think about it: two people can have the same BMI, but one might be very muscular with little fat, while the other might have very little muscle and a lot of fat. This is especially problematic in conditions like sarcopenia (muscle loss) with concomitant fat gain, often called sarcopenic obesity, which BMI simply cannot detect. This lack of detail can have “misleading or deleterious effects on the treatment planning and monitoring of cancer patients”.
The study visually demonstrated this heterogeneity. For example, patients classified as “underweight” or “normal” based on their BMI percentile could actually have significantly more subcutaneous adipose tissue (SAT, or fat just under the skin) and less skeletal muscle (SkM) compared to patients in higher BMI categories. In one extreme case from the study, an underweight patient (0th BMI percentile) was found to have 40.4% SAT, while an obese patient (97th BMI percentile) had 33.9% SAT. This striking example, along with others presented in the study, clearly shows that BMI percentiles can be a highly misleading classification tool when evaluating actual body composition.
The Power of CT Imaging: A Closer Look Inside
So, if BMI isn’t sufficient, what’s a better approach? The answer, according to Tram and colleagues, lies in standard of care computed tomography (CT) imaging.
CT imaging, or magnetic resonance (MR) imaging, can accurately quantify measures of skeletal muscle (SkM), subcutaneous adipose tissue (SAT), and visceral adipose tissue (VAT). VAT is fat around your organs, and it’s particularly important because it’s linked to various health issues. While other techniques like bioelectrical impedance or DXA (Dual-energy X-ray absorptiometry) can give some body composition insights, they don’t differentiate between SAT and VAT, or they can’t quantify VAT at all. The real advantage of CT (or MR) is that these images are often already being acquired during the course of cancer treatment for other purposes, meaning no additional testing or radiation exposure is needed just for body composition assessment.
What the Study Revealed: Hidden Changes in Young Lymphoma Patients
The Tram et al. study focused on 110 pediatric and AYA patients (aged 2 to 21 years) with lymphoma treated at Nationwide Children’s Hospital between 2010 and 2019. Researchers used low-dose CT images taken at two key time points:
- Baseline: Before starting any treatment.
- First Therapeutic Follow-up: 4 to 20 weeks after starting treatment.
They manually segmented five consecutive abdominal CT images at the third lumbar vertebra (L3) level to quantify volumes of SAT, VAT, and SkM. This specific location for analysis has been validated to correlate strongly with whole-body tissue measurements.
Here’s what they found:
- Significant Body Composition Changes: CT imaging detected significant treatment-induced changes in body composition measures from baseline to the first follow-up.
- SAT and VAT significantly increased. On a population level, SAT increased from 40.3% to 42.8%, and VAT increased from 11.5% to 16.3%.
- SkM significantly decreased. On average, SkM decreased from 48.2% to 41.0%.
- BMI Missed These Changes: In stark contrast, BMI percentiles did not change significantly from baseline to first follow-up. Furthermore, changes in BMI% did not significantly correlate with any of the image-derived body composition changes. This is a critical takeaway: the patient’s body was undergoing substantial internal shifts, yet their BMI remained stable.
- Patient Characteristics Matter: The study also identified specific groups of patients who experienced even more pronounced changes:
- Males gained more adipose tissue and lost more SkM compared to females.
- Patients younger than 12 years old gained significantly more adipose tissue and lost more SkM compared to older patients.
- Those diagnosed with Non-Hodgkin’s lymphoma experienced greater adipose tissue gain and SkM loss.
- Patients with more advanced disease (Stage 3 or 4) gained significantly more VAT and lost more SkM compared to those with earlier stages (Stage 1 or 2).
Why This Matters for the Future of Cancer Care
The findings from Tram et al. (2022) have profound implications for how we monitor and treat young cancer patients:
- Early Detection of Toxicity: The study found these significant body composition changes occurred early in treatment, within weeks or months of diagnosis. This means that CT imaging can provide a more sensitive approach for monitoring treatment-induced toxicity than BMI.
- Personalized Treatment Approaches: Understanding these shifts in muscle and fat allows for more personalized approaches to lymphoma treatment. If clinicians know a patient is rapidly losing muscle or gaining unhealthy fat, they could adjust dietary and exercise recommendations, or even chemotherapy dosing regimens, to prevent undesirable changes and enhance clinical outcomes.
- Identifying At-Risk Patients: By identifying patients at risk of developing conditions like obesity or sarcopenia, clinicians might gain insight into the “most ideal, personalized chemotherapy dosing regimens that prevent overtreatment and/or adverse effects of therapy”.
- Filling a Research Gap: This study is significant because body composition in pediatric and AYA oncology, especially in lymphomas, has been understudied. It lays the groundwork for future research to explore the role of body composition in moderating treatment outcomes.
While this study was retrospective and conducted at a single site, the findings strongly advocate for incorporating routine CT imaging for body composition assessment in clinical practice. This approach could truly revolutionize how we support young cancer patients, moving beyond the limitations of simple weight and BMI to understand the complex, dynamic changes happening within their bodies during treatment. It’s about seeing the full picture to provide the best possible care.