Body composition predictors of mortality on computed tomography in patients with spinal metastases undergoing surgical treatment

Malnutrition in Spine Oncology: Where Are We and What Are We Measuring?

STUDY DESIGN

Scoping review.

OBJECTIVE

To identify which markers are used as surrogates for malnutrition in metastatic spine disease and which are the most studied outcomes associated with it.

METHODS

A scoping review was performed by searching the PubMed/Medline, EMBASE, and Web of Science databases up to July 2022. We searched for articles exploring markers of malnutrition in spine oncology patients including but not limited to albumin, body weight, weight loss, and nutrition indices. A narrative synthesis was performed.

RESULTS

A total of 61 articles reporting on 31,385 patients met inclusion criteria. There were 13 different surrogate markers of nutrition, with the most common being albumin in 67% of studies (n = 41), body weight/BMI in 34% (n = 21), and muscle mass in 28% (n = 17). The most common studied outcomes were survival in 82% (n = 50), complications in 28% (n = 17), and length of stay in 10% (n = 6) of studies. Quality of life and functional outcomes were assessed in 2% (n = 1) and 3% (n = 2) of studies, respectively. Out of 61 studies, 18% (n = 11) found no association between the examined markers and outcome.

CONCLUSION

Assessment of nutritional status in patients with spinal metastases is fundamental. However, there is lack of a comprehensive and consistent way of assessing malnutrition in oncologic spine patients and therefore inconsistency in its relationship with outcomes. A consensus agreement on the assessment and definition of malnutrition in spine tumor patients is needed.

Oncologic Applications of Artificial Intelligence and Deep Learning Methods in CT Spine Imaging-A Systematic Review

In spinal oncology, integrating deep learning with computed tomography (CT) imaging has shown promise in enhancing diagnostic accuracy, treatment planning, and patient outcomes. This systematic review synthesizes evidence on artificial intelligence (AI) applications in CT imaging for spinal tumors. A PRISMA-guided search identified 33 studies: 12 (36.4%) focused on detecting spinal malignancies, 11 (33.3%) on classification, 6 (18.2%) on prognostication, 3 (9.1%) on treatment planning, and 1 (3.0%) on both detection and classification. Of the classification studies, 7 (21.2%) used machine learning to distinguish between benign and malignant lesions, 3 (9.1%) evaluated tumor stage or grade, and 2 (6.1%) employed radiomics for biomarker classification. Prognostic studies included three (9.1%) that predicted complications such as pathological fractures and three (9.1%) that predicted treatment outcomes. AI's potential for improving workflow efficiency, aiding decision-making, and reducing complications is discussed, along with its limitations in generalizability, interpretability, and clinical integration. Future directions for AI in spinal oncology are also explored. In conclusion, while AI technologies in CT imaging are promising, further research is necessary to validate their clinical effectiveness and optimize their integration into routine practice.

Sarcopenia and the management of spinal disease in the elderly

Sarcopenia, generally defined by the loss of skeletal mass and function, may disproportionately affect elderly individuals and heavily influence spinal disease. Muscle atrophy is associated with myriad clinical problems, including thoracic kyphosis, increased sagittal vertical axis (SVA), spinal implant failures, and postoperative complications. As such, the aim of this narrative review is to synthesize pertinent literature detailing the intersection between sarcopenia and the impact of sarcopenia on the management of spine disease. Specifically, we focus on the domains of etiology, diagnosis and assessment, impact on the cervical and lumbar spine, spinal augmentation procedures, neoplastic disease, whiplash injury, and recovery/prevention. A narrative review was conducted by searching the PubMed and Google Scholar databases from inception to July 12, 2024, for any cohort studies, systematic reviews, or randomized controlled trials. Case studies and conference abstracts were excluded. Diagnosis of sarcopenia relies on the assessment of muscle strength and quantity/quality. Strength may be assessed using clinical tools such as gait speed, timed up and go (TUG) test, or hand grip strength, whereas muscle quantity/quality may be assessed via computed tomography (CT scan), magnetic resonance imaging (MRI), and dual-energy X-ray absorptiometry (DXA scan). Sarcopenia has a generally negative impact on the clinical course of those undergoing cervical and lumbar surgery, and may be predictive of mortality in those with neoplastic spinal disease. In addition, severe acceleration-deceleration (whiplash) injuries may result in cervical extensor muscle atrophy. Intervention and recovery measures include nutrition or exercise therapy, although the evidence for nutritional intervention is lacking. Sarcopenia is a widely prevalent pathology in the advanced-age population, in which the diagnostic criteria, impact on spinal pathology, and recovery/prevention measures remain understudied. However, further understanding of this therapeutically challenging pathology is paramount, as surgical outcome may be heavily influenced by sarcopenia status.

Opportunistic CT for Prediction of Adverse Postoperative Events in Patients with Spinal Metastases

The purpose of this study was to assess the value of body composition measures obtained from opportunistic abdominal computed tomography (CT) in order to predict hospital length of stay (LOS), 30-day postoperative complications, and reoperations in patients undergoing surgery for spinal metastases. 196 patients underwent CT of the abdomen within three months of surgery for spinal metastases. Automated body composition segmentation and quantifications of the cross-sectional areas (CSA) of abdominal visceral and subcutaneous adipose tissue and abdominal skeletal muscle was performed. From this, 31% (61) of patients had postoperative complications within 30 days, and 16% (31) of patients underwent reoperation. Lower muscle CSA was associated with increased postoperative complications within 30 days (OR [95% CI] = 0.99 [0.98-0.99], p = 0.03). Through multivariate analysis, it was found that lower muscle CSA was also associated with an increased postoperative complication rate after controlling for the albumin, ASIA score, previous systemic therapy, and thoracic metastases (OR [95% CI] = 0.99 [0.98-0.99], p = 0.047). LOS and reoperations were not associated with any body composition measures. Low muscle mass may serve as a biomarker for the prediction of complications in patients with spinal metastases. The routine assessment of muscle mass on opportunistic CTs may help to predict outcomes in these patients.

Determining patients with spinal metastases suitable for surgical intervention: A cost-effective analysis

BACKGROUND

Both nonoperative and operative treatments for spinal metastasis are expensive interventions. Patients' expected 3-month survival is believed to be a key factor to determine the most suitable treatment. However, to the best of our knowledge, no previous study lends support to the hypothesis. We sought to determine the cost-effectiveness of operative and nonoperative interventions, stratified by patients' predicted probability of 3-month survival.

METHODS

A Markov model with four defined health states was used to estimate the quality-adjusted life years (QALYs) and costs for operative intervention with postoperative radiotherapy and radiotherapy alone (palliative low-dose external beam radiotherapy) of spine metastases. Transition probabilities for the model, including the risks of mortality and functional deterioration, were obtained from secondary and our institutional data. Willingness to pay thresholds were prespecified at $100,000 and $150,000. The analyses were censored after 5-year simulation from a health system perspective and discounted outcomes at 3% per year. Sensitivity analyses were conducted to test the robustness of the study design.

RESULTS

The incremental cost-effectiveness ratios were $140,907 per QALY for patients with a 3-month survival probability >50%, $3,178,510 per QALY for patients with a 3-month survival probability <50%, and $168,385 per QALY for patients with independent ambulatory and 3-month survival probability >50%.

CONCLUSIONS

This study emphasizes the need to choose patients carefully and estimate preoperative survival for those with spinal metastases. In addition to reaffirming previous research regarding the influence of ambulatory status on cost-effectiveness, our study goes a step further by highlighting that operative intervention with postoperative radiotherapy could be more cost-effective than radiotherapy alone for patients with a better survival outlook. Accurate survival prediction tools and larger future studies could offer more detailed insights for clinical decisions.

Body Composition Predictors of Adverse Postoperative Events in Patients Undergoing Surgery for Long Bone Metastases

Body composition assessed using opportunistic CT has been recently identified as a predictor of outcome in patients with cancer. The purpose of this study was to determine whether the cross-sectional area (CSA) and the attenuation of abdominal subcutaneous adipose tissue, visceral adipose tissue (VAT), and paraspinous and abdominal muscles are the predictors of length of hospital stay, 30-day postoperative complications, and revision surgery in patients treated for long bone metastases.