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STUDY DESIGN: Retrospective cohort study. OBJECTIVE: In general, Multiple Myeloma (MM) patients are treated with systemic therapy including chemotherapy. Radiation therapy can have an important supportive role in the palliative management of MM-related osteolytic lesions. Our study aims to investigate the degree of radiation-induced remineralization in MM patients to gain a better understanding of its potential impact on bone mineral density and, consequently, fracture prevention. Our primary outcome measure was percent change in bone mineral density measured in Hounsfield Units (Δ% HU) between pre- and post-radiation measurements, compared to non-targeted vertebrae. METHODS: We included 119 patients with MM who underwent radiotherapy of the spine between January 2010 and June 2021 and who had a CT scan of the spine at baseline and between 3-24 months after radiation. A linear mixed effect model tested any differences in remineralization rate per month (ßdifference) between targeted and non-targeted vertebrae. RESULTS: Analyses of CT scans yielded 565 unique vertebrae (366 targeted and 199 non-targeted vertebrae). In both targeted and non-targeted vertebrae, there was an increase in bone density per month (ßoverall = .04; P = .002) with the largest effect being between 9-18 months post-radiation. Radiation did not cause a greater increase in bone density per month compared to non-targeted vertebrae (ßdifference = .67; P = .118). CONCLUSION: Our results demonstrate that following radiation, bone density increased over time for both targeted and non-targeted vertebrae. However, no conclusive evidence was found that targeted vertebrae have a higher remineralization rate than non-targeted vertebrae in patients with MM.
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BACKGROUND CONTEXT: Conventional external beam radiation therapy (cEBRT) is used in multiple myeloma (MM) to treat severe pain, spinal cord compression, and disease-related bone disease. However, radiation may be associated with an increased risk of vertebral compression fractures (VCFs), which could substantially impair survival and quality of life. Additionally, the use of the Spinal Instability Neoplastic Score (SINS) in MM is debated in MM. PURPOSE: To determine the incidence of VCFs after cEBRT in patients with MM and to assess the applicability of the SINS score in the prediction of VCFs in MM. STUDY DESIGN: Retrospective multicenter cohort study. PATIENT SAMPLE: MM patients with spinal myeloma lesions who underwent cEBRT between January 2010 and December 2021. OUTCOME MEASURES: Frequency of new or progressed VCFs and subdistribution hazard ratios for potentially associated factors. METHODS: Patient and treatment characteristics were manually collected from the patients' electronic medical records. Computed tomography (CT) scans from before and up to 3 years after the start of radiation were used to score radiographic variables at baseline and at follow-up. Multivariable Fine and Gray competing risk analyses were performed to evaluate the diagnostic value of the SINS score to predict the postradiation VCF rate. RESULTS: A total of 127 patients with 427 eligible radiated vertebrae were included in this study. The mean age at radiation was 64 years, and 66.1% of them were male. At the start of radiation, 57 patients (44.9%) had at least one VCF. There were 89 preexisting VCFs (18.4% of 483 vertebrae). Overall, 39 of 127 patients (30.7%) reported new fractures (number of vertebrae (n)=12) or showed progression of existing fractures (n=36). This number represented 11.2% of all radiated vertebrae. Five of the 39 (12.8%) patients with new or worsened VCFs received an unplanned secondary treatment (augmentation [n=2] or open surgery [n=3]) within 3 years. Both the total SINS score (SHR 1.77; 95% confidence interval (CI) 1.54-2.03; p<.001) and categorical SINS score (SHR 10.83; 95% CI 4.20-27.94; p<.001) showed an independent association with higher rates of new or progressed VCFs in adjusted analyses. The use of bisphosphonates was independently associated with a lower rate of new or progressed VCFs (SHR 0.47 [95% CI 0.24-0.92; p=.027]). CONCLUSIONS: This study demonstrated that new or progressed VCFs occurred in 30.7% of patients within 3 years, in a total of 11.2% of vertebrae. The SINS score was found to be independently associated with the development or progression of VCFs and could thus be applied in MM for fracture prediction and possibly prevention.
Subject(s)
Fractures, Compression , Multiple Myeloma , Spinal Fractures , Humans , Male , Female , Spinal Fractures/diagnostic imaging , Spinal Fractures/epidemiology , Spinal Fractures/etiology , Fractures, Compression/diagnostic imaging , Fractures, Compression/epidemiology , Fractures, Compression/etiology , Multiple Myeloma/epidemiology , Multiple Myeloma/radiotherapy , Multiple Myeloma/complications , Cohort Studies , Quality of Life , Spine , Retrospective StudiesABSTRACT
STUDY DESIGN: Retrospective cohort study. OBJECTIVES: Up to 30% of Multiple Myeloma (MM) patients are expected to experience Epidural Spinal Cord Compression (ESCC) during the course of their disease. To prevent irreversible neurological damage, timely diagnosis and treatment are important. However, debate remains regarding the optimal treatment regimen. The aim of this study was to investigate the neurological outcomes and frequency of retreatments for MM patients undergoing isolated radiotherapy and surgical interventions for high-grade (grade 2-3) ESCC. METHODS: This study included patients with MM and high-grade ESCC treated with isolated radiotherapy or surgery. Pre- and post-treatment American Spinal Injury Association (ASIA) impairment scale and retreatment rate were compared between the 2 groups. Adjusted multivariable logistic regression was utilized to examine differences in neurologic compromise, pain, and retreatments. RESULTS: A total of 247 patients were included (Radiotherapy: n = 154; Surgery: n = 93). After radiotherapy, 82 patients (53%) achieved full neurologic function (ASIA E) at the end of follow-up. Of the surgically treated patients, 67 (64%) achieved full neurologic function. In adjusted analyses, patients treated with surgery were less likely to experience neurologic deterioration within 2 years (OR = .15; 95%CI .05-.44; P = .001) and had less pain (OR = .29; 95%CI .11-.74; P = .010). Surgical treatment was not associated with an increased risk of retreatments (OR = .64; 95%CI .28-1.47; P = .29) or death (HR = .62, 95%CI .28-1.38; P = .24). CONCLUSIONS: After adjusting for baseline differences, surgically treated patients with high-grade ESCC showed better neurologic outcomes compared to patients treated with radiotherapy. There were no differences in risk of retreatment or death.
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BACKGROUND: Artificial intelligence (AI) tremendously influences our daily lives and the medical field, changing the scope of medicine. One of the fields where AI, and, in particular, predictive modeling, holds great promise is spinal oncology. An accurate patient prognosis is essential to determine the optimal treatment strategy for patients with spinal metastases. Multiple studies demonstrated that the physician's survival predictions are inaccurate, which resulted in the development of numerous predictive models. However, difficulties arise when trying to interpret these models and, more importantly, assess their quality. OBJECTIVE: To provide an overview of all stages and challenges in developing predictive models using the Skeletal Oncology Research Group machine learning algorithms as an example. METHODS: A narrative review of all relevant articles known to the authors was conducted. RESULTS: Building a predictive model consists of 6 stages: preparation, development, internal validation, presentation, external validation, and implementation. During validation, the following measures are essential to assess the model's performance: calibration, discrimination, decision curve analysis, and the Brier score. The structured methodology in developing, validating, and reporting the model is vital when building predictive models. Two principal guidelines are the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis checklist and the prediction model risk of bias assessment. To date, many predictive modeling studies lack the right validation measures or improperly report their methodology. CONCLUSIONS: A new health care age is being ushered in by the rapid advancement of AI and its applications in spinal oncology. A myriad of predictive models are being developed; however, the subsequent stages, quality of validation, transparent reporting, and implementation still need improvement. CLINICAL RELEVANCE: Given the rapid rise and use of AI prediction models in patient care, it is valuable to know how to assess their quality and to understand how these models influence clinical practice. This article provides guidance on how to approach this.
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INTRODUCTION: There are predictive algorithms for predicting 3-month and 1-year survival in patients with spinal metastasis. However, advance in surgical technique, immunotherapy, and advanced radiation therapy has enabled shortening of postoperative recovery, which returns dividends to the overall quality-adjusted life-year. As such, the Skeletal Oncology Research Group machine learning algorithm (SORG-MLA) was proposed to predict 6-week survival in patients with spinal metastasis, whereas its utility for patients treated with nonsurgical treatment was untested externally. This study aims to validate the survival prediction of the 6-week SORG-MLA for patients with spinal metastasis and provide the measurement of model consistency (MC). METHODS: Discrimination using area under the receiver operating characteristic curve, calibration, Brier score, and decision curve analysis were conducted to assess the model's performance in the Taiwanese-based cohort. MC was also applied to detect the proportion of paradoxical predictions among 6-week, 3-month, and 1-year survival predictions. The long-term prognosis should not be better than the shorter-term prognosis in that of an individual. RESULTS: The 6-week survival rate was 84.2%. The SORG-MLA retained good discrimination with an area under the receiver operating characteristic curve of 0.78 (95% confidence interval, 0.75 to 0.80) and good prediction accuracy with a Brier score of 0.11 (null model Brier score 0.13). There is an underestimation of the 6-week survival rate when the predicted survival rate is less than 50%. Decision curve analysis showed that the model was suitable for use over all threshold probabilities. MC showed suboptimal consistency between 6-week and 90-day survival prediction (78%). CONCLUSIONS: The results of this study supported the utility of the algorithm. The online tool ( https://sorg-apps.shinyapps.io/spinemetssurvival/ ) can be used by both clinicians and patients in informative decision-making discussion before management of spinal metastasis.
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Spinal Neoplasms , Humans , Prognosis , Algorithms , Machine Learning , Survival Rate , Retrospective StudiesABSTRACT
Background: Multiple myeloma (MM) is a hematologic malignancy, characterized by clonal proliferation of plasma cells in the bone marrow. These plasma cell proliferations frequently result in scattered osteolytic bone lesions and extensive skeletal destruction. Myeloma bone lesions are frequently located in the spine, and are associated with debilitating bone pain and an increased rate of pathologic fractures and mortality. The aim of this study was to investigate the incidence of vertebral compression fractures (VCFs) and spinal instability in patients with MM. Patients and methods: Newly diagnosed patients with MM with computed tomography (CT) scans of the spine within three months of diagnosis were identified through an electronic patient database. Clinical baseline data were manually extracted from the patient charts. Fractured levels were graded on CT scans following the Genant grading system, and spinal instability was assessed through the Spinal Instability Neoplastic Score (SINS). Results: A total of 385 patients with 6289 eligible vertebrae were eligible for inclusion. The mean age at diagnosis was 67 years, and 60% were male. At least one VCF was present in 180 patients (47%). A quarter of fractures were classified as severe. The incidence of fractures increased with more advanced disease stages, and men were more likely to have a fracture than women. Conclusions: Our data show that 47% of MM patients present with one or more VCFs at the onset of their disease, of which 20% were classified as unstable, meaning a surgical consultation is recommended.
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BACKGROUND AND PURPOSE: Well-performing survival prediction models (SPMs) help patients and healthcare professionals to choose treatment aligning with prognosis. This retrospective study aims to investigate the prognostic impacts of laboratory data and to compare the performances of Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy (METSSS) model, New England Spinal Metastasis Score (NESMS), and Skeletal Oncology Research Group machine learning algorithm (SORG-MLA) for spinal metastases (SM). MATERIALS AND METHODS: From 2010 to 2018, patients who received radiotherapy (RT) for SM at a tertiary center were enrolled and the data were retrospectively collected. Multivariate logistic and Cox-proportional-hazard regression analyses were used to assess the association between laboratory values and survival. The area under receiver-operating characteristics curve (AUROC), calibration analysis, Brier score, and decision curve analysis were used to evaluate the performance of SPMs. RESULTS: A total of 2786 patients were included for analysis. The 90-day and 1-year survival rates after RT were 70.4% and 35.7%, respectively. Higher albumin, hemoglobin, or lymphocyte count were associated with better survival, while higher alkaline phosphatase, white blood cell count, neutrophil count, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, or international normalized ratio were associated with poor prognosis. SORG-MLA has the best discrimination (AUROC 90-day, 0.78; 1-year 0.76), best calibrations, and the lowest Brier score (90-day 0.16; 1-year 0.18). The decision curve of SORG-MLA is above the other two competing models with threshold probabilities from 0.1 to 0.8. CONCLUSION: Laboratory data are of prognostic significance in survival prediction after RT for SM. Machine learning-based model SORG-MLA outperforms statistical regression-based model METSSS model and NESMS in survival predictions.
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Spinal Neoplasms , Humans , Aged , Prognosis , Spinal Neoplasms/radiotherapy , Spinal Neoplasms/secondary , Retrospective Studies , Alkaline Phosphatase , AlbuminsABSTRACT
BACKGROUND CONTEXT: Preoperative embolization (PE) reduces intraoperative blood loss during surgery for spinal metastases of hypervascular primary tumors such as thyroid and renal cell tumors. However, most spinal metastases originate from primary breast, prostate, and lung tumors and it remains unclear whether these and other spinal metastases benefit from PE. PURPOSE: To assess the (1) efficacy of PE on the amount of intraoperative blood loss and safety in patients with spinal metastases originating from non-hypervascular primary tumors, and (2) secondary outcomes including perioperative allogeneic blood transfusion, anesthesia time, hospitalization, postoperative complication within 30 days, reoperation, 90-day mortality, and 1-year mortality. STUDY DESIGN: Retrospective propensity-score matched, case-control study at 2 academic tertiary medical centers. PATIENT SAMPLE: Patients 18 years of age or older undergoing surgery for spinal metastases originating from primary non-thyroid, non-renal cell, and non-hepatocellular tumors between January 1, 2002 and December 31, 2016 were included. OUTCOME MEASURES: The primary outcomes were estimated amount of intraoperative blood loss and complications attributable to PE, such as neurologic injury, wound infection, thrombosis, or dissection. The secondary outcomes included perioperative allogeneic blood transfusion, anesthesia time, hospitalization, postoperative complication within 30 days, reoperation, 90-day mortality, and 1-year mortality. METHODS: In total, 495 patients were identified, of which 54 (11%) underwent PE. After propensity score matching on 21 variables, including primary tumor, number of spinal levels, and surgical treatment, 53 non-PE patients were matched to 53 PE patients. Matching was adequate measured by comparing the matched variables, testing the standardized mean differences (<0.25), and inspecting Kernel density plots. The degree of embolization was noted to be complete, until stasis, or successful in 43 (80%) patients. RESULTS: Intraoperative blood loss did not differ between both groups with a median blood loss in liters of 0.6 (IQR, 0.4-1.2) for non-PE patients and 0.9 (IQR, 0.6-1.2) for PE patients (p=.32). No complications occurred during embolization or the time between embolization and surgery. No differences were found in terms of the secondary outcomes. CONCLUSIONS: Our data suggest that, although no complications occurred and the embolization procedure can be considered safe, patients with non-hypervascular spinal metastases might not benefit from PE. A larger, prospective study could confirm or refute these study findings and aid in elucidating a subset of spinal metastases that might benefit from PE.
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Embolization, Therapeutic , Kidney Neoplasms , Spinal Neoplasms , Adolescent , Adult , Blood Loss, Surgical/prevention & control , Case-Control Studies , Embolization, Therapeutic/adverse effects , Embolization, Therapeutic/methods , Humans , Kidney Neoplasms/complications , Kidney Neoplasms/surgery , Male , Postoperative Complications , Preoperative Care/methods , Propensity Score , Prospective Studies , Retrospective Studies , Spinal Neoplasms/secondary , Treatment OutcomeABSTRACT
BACKGROUND CONTEXT: Spondylodiscitis is the most common spinal infection of which the incidence has increased and the peak prevalence is between 50 and 70 years of age. Spondylodiscitis is often a complication of a distant infection. Early diagnosis can be challenging, and although improvements in diagnostic techniques and modern therapy have diminished the mortality of the disease, current literature about the outcome of spondylodiscitis is scarce. PURPOSE: To evaluate the long-term clinical outcome of patients who suffered from spondylodiscitis. STUDY DESIGN: A two-center cross-sectional study. PATIENT SAMPLE: Patients with spondylodiscitis in two large teaching hospitals in the Netherlands between 2003 and 2017. OUTCOME MEASURES: Visual Analogue Scale (VAS) for back pain, Oswestry Disability Index (ODI) for function, and Short Form 36 (SF-36) for general quality of life of spondylodiscitis patients. METHOD: Eligible patients were identified from electronic patient databases and completed multiple patient reported outcome measures after obtaining informed consent. General demographic and clinical information (age, sex, medical history) were extracted from the patient records. SF-36 domain scores of spondylodiscitis patients were compared with a nationwide population sample. RESULTS: 183 patients were treated for spondylodiscitis; additional questionnaires were received from 82 patients. After a median follow-up of 63 months, the overall mortality was 28%. The mean VAS for back pain was 3.5, and the mean ODI score was 22. In all SF-36 domains a significantly lower score was found in the spondylodiscitis group compared with a normative national Dutch cohort. There was a strong correlation between back pain and ODI scores (ρ=0.81, p<.05). CONCLUSIONS: Our study confirms that spondylodiscitis is a disease causing a profound impact on back pain, function and quality of life. The results suggest that chronic back pain is a debilitating problem, as it has an extensive influence on daily activities and social and psychological well-being, causing significant disability.
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Discitis , Quality of Life , Cross-Sectional Studies , Disability Evaluation , Discitis/epidemiology , Humans , Pain Measurement , Treatment OutcomeABSTRACT
BACKGROUND CONTEXT: Vertebral compression fractures (VCFs) are a common complication for patients with multiple myeloma. These fractures are associated with significant morbidity and mortality due to severe back pain, spinal instability, increased risk of new fractures, neurologic dysfunction, and other physical symptoms. PURPOSE: To identify risk factors associated with the development of VCFs which may help to predict them in future patients. STUDY DESIGN: A retrospective multicenter cohort study. PATIENT SAMPLE: Patients with multiple myeloma diagnosed between 2012 and 2018 and appropriate baseline- and follow-up imaging studies (>6 months after diagnosis) were included. OUTCOME MEASURES: Individual odds ratios for each of the fifteen potential risk factors including patient factors and radiographical characteristics. METHODS: Relevant clinical baseline data were extracted from the patient charts. Computed tomography (CT) scans were used to score all radiographic variables. VCFs were graded following the Genant grading system. General Linear Mixed Models were used to analyze risk factors associated with vertebral fractures. RESULTS: A total of 143 patients with 1,605 eligible vertebrae were included in the study with a mean follow-up time of 25 months. Mean age at diagnosis was 65 years and 39% were female. Among 1,605 vertebrae, there were 192 (12%) VCFs (Genant grade 1 or higher) at the time of diagnosis and 111 (7%) occurred during follow-up. In a General Linear Mixed Model, significant predictors were gender (odds ratio [OR]=1.5), International Staging System stage 2 and 3 (OR=3.6 and OR=4.1 respectively), and back pain (OR=2.7). Furthermore, lower Hounsfield Unit score, lytic lesions and abnormal alignment were risk factors for (the development of) VCFs. CONCLUSIONS: This study investigated both patient characteristics and vertebra-specific risk factors for VFCs in multiple myeloma patients. The factors found in this study might be useful for identifying patients at higher risk of VFCs to help clinical management to prevent vertebral collapse and the development of spinal deformities.
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Fractures, Compression , Multiple Myeloma , Spinal Fractures , Cohort Studies , Female , Fractures, Compression/diagnostic imaging , Fractures, Compression/epidemiology , Fractures, Compression/etiology , Humans , Male , Multiple Myeloma/complications , Multiple Myeloma/diagnostic imaging , Multiple Myeloma/epidemiology , Retrospective Studies , Spinal Fractures/diagnostic imaging , Spinal Fractures/epidemiology , Spinal Fractures/etiology , Treatment OutcomeABSTRACT
The stereodivergent ring-opening of 2-phenyl oxazaphospholidines with alkyl lithium reagents is reported. N-H oxazaphospholidines derived from both (+)-cis-1-amino-2-indanol and (-)-norephedrine provide inversion products in a highly stereoselective process. In contrast, N-Me oxazaphospholidines yield ring-opening products with retention of configuration at the P center, as previously reported by Jugé and co-workers. As a result, from a single amino alcohol auxiliary, both enantiomers of key P-stereogenic intermediates could be synthesized. Theoretical studies of ring-opening with model oxazaphospholidines at the DFT level have elucidated the streochemical course of this process. N-H substrates react in a single step via preferential backside S(N)2@P substitution with inversion at phosphorus. N-methylated substrates react preferentially via a two-step frontside S(N)2@P, yielding a ring-opened product in which the nucleophilic methyl binds to P with retention of configuration. DFT calculations have shown that the BH3 unit is a potent directing group to which the methyl lithium reagent coordinates via Li in all the reactions studied.
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Benzene Derivatives/chemistry , Boranes/chemistry , Oxazoles/chemistry , Indans/chemistry , Lithium/chemistry , Models, Molecular , Phenylpropanolamine/chemistry , Phosphorus/chemistry , StereoisomerismABSTRACT
We show that the cooperative reinforcement between hydrogen bonds in guanine quartets is not caused by resonance-assisted hydrogen bonding (RAHB). This follows from extensive computational analyses of guanine quartets (G(4)) and xanthine quartets (X(4)) based on dispersion-corrected density functional theory (DFT-D). Our investigations cover the situation of quartets in the gas phase, in aqueous solution as well as in telomere-like stacks. A new mechanism for cooperativity between hydrogen bonds in guanine quartets emerges from our quantitative Kohn-Sham molecular orbital (MO) and corresponding energy decomposition analyses (EDA). Our analyses reveal that the intriguing cooperativity originates from the charge separation that goes with donor-acceptor orbital interactions in the σ-electron system, and not from the strengthening caused by resonance in the π-electron system. The cooperativity mechanism proposed here is argued to apply, beyond the present model systems, also to other hydrogen bonds that show cooperativity effects.