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Advances in immunotherapy have significantly improved outcomes for patients with advanced or metastatic non-small cell lung cancer (NSCLC). However, predicting individual responses to these therapies is still challenging. Recent research has focused on the prognostic value of body composition metrics, including body mass index (BMI), skeletal muscle (SM) mass, and adipose tissue distribution, which may aid in predicting treatment outcomes.^1,2

Using AI-assisted workflow

In their study, first author, Tafadzwa L. Chaunzwa, MD, and corresponding author, Hugo J.W.L. Aerts, PhD, both of the Artificial Intelligence in Medicine Program, Mass General Brigham and Department of Radiation Oncology, Dana Farber Cancer Institute, Brigham and Women鈥檚 Hospital, Harvard Medical School, Boston, Massachusetts, examined the prognostic role of body composition using deep learning with automation of extraction of body composition measurements from computed tomography (CT). The findings were published online in JAMA Oncology. 

This was a retrospective study with data from 2 previously completed trials, the phase 3 MYSTIC trial with patients receiving standard-of-care first-line chemotherapy, and 2 cohorts from the Dana-Farber Brigham Cancer Center (DFBCC), 1 having received chemoimmunotherapy, and 1 that had received immunotherapy monotherapy.¹ Data were collected from CT imaging prior to the beginning of therapy and 4-8 weeks after treatment was started.¹ The body composition metrics were then determined using an artificial intelligence-assisted workflow.¹ The investigators then explored the associations between these measures and overall survival (OS) and progression-free survival (PFS).¹ Of the patients included, 27.2% had been administered a combination of immune checkpoint inhibitors (ICIs) and chemotherapy, 58.5% had received immunotherapy alone, and 14.3% had received chemotherapy alone.¹

Key findings from the chemoimmunotherapy cohort

Men had higher baseline skeletal muscle density (SMd) and visceral adipose tissue (VAT) compared to women, whereas women had higher baseline subcutaneous adipose tissue (SAT). The baseline SMd was found to be significantly associated with OS (HR 0.991; 95% CI, 0.983-0.999; P=.03). The changes in parameters were found to be important prognostic markers. The changes in SM area (SMa) (HR 0.589; 95% CI, 0.428-0.811; P=.001) and SATd (HR 0.606; 95% CI, 0.427-0.861; P<.05), were most strongly associated with OS; the changes in SMa (HR 0.609; 95% CI, 0.467- 0.793; P< .001) and SATd (HR 0.725; 95 CI, 0.539-0.9739; P=.03) were associated with PFS. A loss of SMa > 5% was associated with a worse OS vs changes in SMa. An increase of > 5% for SATd was associated with worse OS and PFS. Conversely, a change of > 5% for SAT was associated with a better OS.¹

Among the chemoimmunotherapy cohort, the clinical measures associated with OS were Eastern Cooperative Oncology Group performance status (PS) (hazard ratio [HR] 1.559; 95% CI, 1.081-2.246; P=.02) and programmed cell death ligand 1 (PD-L1) status (HR 0.992; 95% CI, 0.986-0.999; P=.04). PD-L1 levels were also associated with PFS (HR 0.991; 95% CI, 0.985-0.997; P=.002).

Insights from the immunotherapy alone cohort

In the DFBCC immunotherapy alone cohort, clinical measures associated with OS were PS, tumor mutational burden, PD-L1 status, and line of therapy. PS (HR 1.448; 95% CI, 1.180-1.775; P<.001) and tumor mutational burden (HR 0.950; 95% CI, 0.930-0.970; P<.001) were also correlated with PFS. Men had higher SMa and VAT vs women, whereas women had higher baseline SAT. The baseline SMd (HR 0.993; 95% CI, 0.987-0.999; P=.03) and SAT (HR 0.998; 95% CI, 0.997-0.999; P<.05) were found to be significantly associated with OS. Changes in SMa (HR 0.740; 95% CI, 0.599-0.914; P<.05) and SATd (HR 0.625; 95% CI, 0.493-0.792; P<.001) were associated with OS. Both a loss of SMa > 5% and an increase in SATd > 5% were associated with a worse OS.¹

The Study 1108 durvalumab cohort was also studied. In this cohort, baseline PS (HR 1.483; 95% CI, 1.136-1.937; P=.004) and PD-L1 status (HR 0.995; 95% CI, 0.992-0.998; P<.001) were associated with OS. PS was also associated with PFS (HR 1.358; 95% CI, 1.046-1.763; P<.05), as was baseline VATd ( HR 1.019; 95% CI, 1.002-1.036; P<.05). The change in SMa was significantly associated with OS (HR, 0.462; 95% CI, 0.334-0.641; P<.001) and PFS (HR, 0.465; 95% CI, 0.337-0.641; P<.001). When the change in SMa was > 5%, there was a significant difference in OS and PFS.¹ The change in SATd was significantly associated with OS (HR, 0.558; 95% CI, 0.402-0.774; P<.001) and PFS (HR, 0.709; 95% CI, 0.529-0.949; P<.05).¹ The change in SATd was significantly associated with OS when it was >5% (P<.001).¹

Prognostic implications with chemotherapy

In the chemotherapy cohort, men had higher baseline SMa and VAT measures. PS was significantly associated with OS (HR 1.436; 95% CI, 1.122- 1.838; P=.004), but not with PFS.¹ The baseline SATd was significantly associated with OS (HR 1.013; 95% CI, 1.004-1.022; P=.004) and PFS (HR 1.009; 95% CI, 1.000- 1.017; P<.05) as was baseline SMd (HR 0.9848; 95% CI, 0.976-0.993; P<.001 and HR 0.991; 95% CI, 0.983-0.999; P<.05, respectively). The change in SMa was significantly associated with PFS (HR 0.761; 95% CI, 0.605-0.959; P<.05), and > 5% loss in SMa was significantly associated with worse OS (P=.03) and PFS (P=.002).¹

Overall measurement prognostics and males vs females

Overall, loss in SM mass and increased SATd were associated with worse outcomes. The changes in parameters were the most significant with > 5% loss in SM mass being significantly associated. This occurred at the highest level in males and especially in patients receiving ICIs. This study appears to suggest a role for monitoring muscle mass in patients being administered systemic therapy for NSCLC, especially in male patients. For females, it is especially key to monitor the SAD, as an increase of > 5% was associated with worse OS when treated with ICIs.¹ Additionally, measuring CT body composition could aid in guiding the treatment of NSCLC with systemic therapy.¹

Limitations

The investigators noted several possible limitations framing the study results. These include the retrospective pooled design with patients receiving varied systemic therapeutic regimens, possibly leading to variations in the responses to treatments. In addition, as many patients were administered ICIs in later lines, it was difficult to infer that the results also apply to those patients receiving first-line therapy. Lastly, the deep learning pipeline was modeled using a small sample, so can not necessarily be used in a large-scale clinical usage.¹

Conclusions and future studies

In conclusion, the authors stated, 鈥淭his multicohort study highlights the significance of loss of SM mass in predicting poor outcomes in patients receiving systemic therapy for advanced NSCLC and reveals an association between changes in SATd and prognosis in female patients treated with ICIs. Further investigations are required to uncover the mechanisms that underlie these associations.鈥�¹

Published: June 28, 2024