A systematic review of evidence on malignant spinal metastases: natural history and technologies for identifying patients at high risk of vertebral fracture and spinal cord compression.Health Technol Assess 2013; 17(42):1-274HT
Spinal metastases can lead to significant morbidity and reduction in quality of life due to spinal cord compression (SCC). Between 5% and 20% of patients with spinal metastases develop metastatic spinal cord compression during the course of their disease. An early study estimated average survival for patients with SCC to be between 3 and 7 months, with a 36% probability of survival to 12 months. An understanding of the natural history and early diagnosis of spinal metastases and prediction of collapse of the metastatic vertebrae are important.
To undertake a systematic review to examine the natural history of metastatic spinal lesions and to identify patients at high risk of vertebral fracture and SCC.
The search strategy covered the concepts of metastasis, the spine and adults. Searches were undertaken from inception to June 2011 in 13 electronic databases [MEDLINE; MEDLINE In-Process & Other Non-Indexed Citations; EMBASE; Cochrane Database of Systematic Reviews; Cochrane Central Register of Controlled Trials (CENTRAL); Database of Abstracts of Reviews of Effects (DARE), NHS Economic Evaluation Database (NHS EED), HTA databases (NHS Centre for Reviews and Dissemination); Science Citation Index and Conference Proceedings (Web of Science); UK Clinical Research Network (UKCRN) Portfolio Database; Current Controlled Trials; ClinicalTrials.gov].
Titles and abstracts of retrieved studies were assessed by two reviewers independently. Disagreement was resolved by consensus agreement. Full data were extracted independently by one reviewer. All included studies were reviewed by a second researcher with disagreements resolved by discussion. A quality assessment instrument was used to assess bias in six domains: study population, attrition, prognostic factor measurement, outcome measurement, confounding measurement and account, and analysis. Data were tabulated and discussed in a narrative review. Each tumour type was looked at separately.
In all, 2425 potentially relevant articles were identified, of which 31 met the inclusion criteria. No study examined natural history alone. Seventeen studies reported retrospective data, 10 were prospective studies, and three were other study designs. There was one systematic review. There were no randomised controlled trials (RCTs). Approximately 5782 participants were included. Sample sizes ranged from 41 to 859. The age of participants ranged between 7 and 92 years. Types of cancers reported on were lung alone (n= 3), prostate alone (n= 6), breast alone (n= 7), mixed cancers (n= 13) and unclear (n= 1). A total of 93 prognostic factors were identified as potentially significant in predicting risk of SCC or collapse. Overall findings indicated that the more spinal metastases present and the longer a patient was at risk, the greater the reported likelihood of development of SCC and collapse. There was an increased risk of developing SCC if a cancer had already spread to the bones. In the prostate cancer studies, tumour grade, metastatic load and time on hormone therapy were associated with increased risk of SCC. In one study, risk of SCC before death was 24%, and 2.37 times greater with a Gleason score ≥ 7 than with a score of < 7 (p= 0.003). Other research found that patients with six or more bone lesions were at greater risk of SCC than those with fewer than six lesions [odds ratio (OR) 2.9, 95% confidence interval (CI) 1.012 to 8.35, p= 0.047]. For breast cancer patients who received a computerised tomography (CT) scan for suspected SCC, multiple logistic regression in one study identified four independent variables predictive of a positive test: bone metastases ≥ 2 years (OR 3.0 95% CI 1.2 to 7.6; p= 0.02); metastatic disease at initial diagnosis (OR 3.4, 95% CI 1.0 to 11.4; p= 0.05); objective weakness (OR 3.8, 95% CI 1.5 to 9.5; p= 0.005); and vertebral compression fracture on spine radiograph (OR 2.6, 95% CI 1.0 to 6.5; p= 0.05). A further study on mixed cancers, among patients who received surgery for SCC, reported that vertebral body compression fractures were associated with presurgery chemotherapy (OR 2.283, 95% CI 1.064 to 4.898; p= 0.03), cancer type [primary breast cancer (OR 4.179, 95% CI 1.457 to 11.983; p= 0.008)], thoracic involvement (OR 3.505, 95% CI 1.343 to 9.143; p= 0.01) and anterior cord compression (OR 3.213, 95% CI 1.416 to 7.293; p= 0.005).
Many of the included studies provided limited information about patient populations and selection criteria and they varied in methodological quality, rigour and transparency. Several studies identified type of cancer (e.g. breast, lung or prostate cancer) as a significant factor in predicting SCC, but it remains difficult to determine the risk differential partly because of residual bias. Consideration of quantitative results from the studies does not easily allow generation of a coherent numerical summary, studies were heterogeneous especially with regard to population, results were not consistent between studies, and study results almost universally lacked corroboration from other independent studies.
No studies were found which examined natural history. Overall burden of metastatic disease, confirmed metastatic bone involvement and immediate symptomatology suggestive of spinal column involvement are already well known as factors for metastatic SCC, vertebral collapse or progression of vertebral collapse. Although we identified a large number of additional possible prognostic factors, those which currently offer the most potential are unclear. Current clinical consensus favours magnetic resonance imaging and CT imaging modalities for the investigation of SCC and vertebral fracture. Future research should concentrate on: (1) prospective randomised designs to establish clinical and quality-of-life outcomes and cost-effectiveness of identification and treatment of patients at high risk of vertebral collapse and SCC; (2) Service Delivery and Organisation research on magnetic resonance imaging (MRI) scans and scanning (in tandem with research studies on use of MRI to monitor progression) in order to understand best methods for maximising use of MRI scanners; and (3) investigation of prognostic algorithms to calculate probability of a specified event using high-quality prospective studies, involving defined populations, randomly selected and clearly identified samples, and with blinding of investigators.
This report was commissioned by the National Institute for Health Research Health Technology Assessment Programme NIHR HTA Programme as project number HTA 10/91/01.