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BACKGROUND: Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided. QUESTIONS/PURPOSES: (1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS? METHODS: Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses. RESULTS: Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS. CONCLUSION: Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments. LEVEL OF EVIDENCE: Level III, diagnostic study.
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OBJECTIVES: Metastatic bone disease is estimated to develop in up to 17% of patients with melanoma, compromising skeleton integrity resulting in skeletal-related events (SREs), which impair quality of life and reduce survival. The objective of the study was to investigate (1) the proportion of melanoma patients developing SREs following diagnosis of bone metastasis and (2) the predictors for SREs in this patient cohort. METHODS: Four hundred and eighty-one patients with bone metastatic melanoma from two tertiary centers in the United States from 2008 to 2018 were included. The primary outcome was 90-day and 1-year occurrence of a SRE, including pathological fractures of bones, cord compression, hypercalcemia, radiotherapy, and surgery. Fine-Gray regression analysis was performed for overall SREs and pathological fracture, with death as a competing risk. RESULTS: By 1-year, 52% (258/481) of patients experienced SREs, and 28% (137/481) had a pathological fracture. At 90-day, lytic lesions, bone pain, elevated calcium and absolute lymphocyte, and decreased albumin and hemoglobin were associated with higher SRE risk. The same factors, except for decreased hemoglobin, were shown to predict development of SREs at 1-year. CONCLUSION: The high incidence of SREs and pathological fractures warrants vigilance using the identified factors in this study and preventative measures during clinical oncological care.
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Neoplasias Ósseas , Fraturas Espontâneas , Melanoma , Humanos , Melanoma/patologia , Melanoma/secundário , Masculino , Neoplasias Ósseas/secundário , Feminino , Estudos Retrospectivos , Pessoa de Meia-Idade , Idoso , Fraturas Espontâneas/etiologia , Seguimentos , Prognóstico , Fatores de Risco , Adulto , Hipercalcemia/etiologia , Taxa de Sobrevida , Neoplasias Cutâneas/patologiaRESUMO
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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INTRODUCTION: Despite the benefits of intramedullary nailing (IMN) of impending or pathologic fractures in oncologic patients, literature on patient-reported outcomes (PROs) is scarce in patients treated with carbon fiber (CF) nails. Our study compared postoperative PROs after IMN with CF or titanium implants. METHODS: We conducted a retrospective propensity score-matched cohort study of patients treated at our institution with CF or titanium nails for impending or pathologic fractures from metastatic bone disease. Patient-Reported Outcomes Measurement Information System (PROMIS) Global Health Short Form (SF) Physical, Mental, and Physical Function 10a scores were collected. Pain was assessed using visual analog scale (VAS). Absolute and differential scores were compared between groups. RESULTS: We included 207 patients, 51 treated with CF and 156 with titanium nails. One month postoperatively, patients had a one-point decrease in the pain VAS score while PROMIS scores did not improve. At 3 months, PROMIS SF Physical and SF 10a scores improved from preoperative values. Six months postoperatively, median PROMIS SF Physical, SF Mental, and SF 10a scores were higher than preoperative scores. Absolute and differential PROMIS and pain VAS scores were similar between groups at the 6-month and 1-year marks. CONCLUSION: Patient-reported outcomes were similar after intramedullary nailing with either CF or titanium implants.
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Pinos Ortopédicos , Neoplasias Ósseas , Fibra de Carbono , Fixação Intramedular de Fraturas , Fraturas Espontâneas , Medidas de Resultados Relatados pelo Paciente , Titânio , Humanos , Masculino , Feminino , Fixação Intramedular de Fraturas/instrumentação , Estudos Retrospectivos , Pessoa de Meia-Idade , Idoso , Fraturas Espontâneas/cirurgia , Neoplasias Ósseas/cirurgia , Pontuação de Propensão , Adulto , Medição da DorRESUMO
OBJECTIVE: Chordomas are rare malignant bone tumors whose location in the skull base or spine, invasive surgical treatment, and accompanying adjuvant radiotherapy may all lead patients to experience poor quality of life (QOL). Limited research has been conducted on specific demographic and clinical factors associated with decreased QOL in chordoma survivors. Thus, the aim of the present study was to investigate several potential variables and their impact on specific QOL domains in these patients as well the frequencies of specific QOL challenges within these domains. METHODS: The Chordoma Foundation (CF) Survivorship Survey was electronically distributed to chordoma survivors subscribed to the CF Chordoma Connections forum. Survey questions assessed QOL in three domains: physical, emotional/cognitive, and social. The degree of impairment was assessed by grouping the participants into high- and low-challenge groups designated by having ≥ 5 or < 5 symptoms or challenges within a given QOL domain. Bivariate analysis of demographic and clinical characteristics between these groups was conducted using Fisher's exact test and the Mann-Whitney U-test. RESULTS: A total of 665 chordoma survivors at least partially completed the survey. On bivariate analysis, female sex was significantly associated with increased odds of significant emotional (p = 0.001) and social (p = 0.019) QOL burden. Younger survivors (age < 65 years) were significantly more likely to experience significant physical (p < 0.0001), emotional (p < 0.0001), and social (p < 0.0001) QOL burden. Skull base chordoma survivors had significantly higher emotional/cognitive QOL burden than spinal chordoma survivors (p = 0.022), while the converse was true for social QOL challenges (p = 0.0048). Survivors currently in treatment were significantly more likely to experience significant physical QOL challenges compared with survivors who completed their treatment > 10 years ago (p = 0.0074). Fear of cancer recurrence (FCR) was the most commonly reported emotional/cognitive QOL challenge (49.6%). Only 41% of the participants reported having their needs met for their physical QOL challenges as well as 25% for emotional/cognitive and 18% for social. CONCLUSIONS: The authors' findings suggest that younger survivors, female survivors, and survivors currently undergoing treatment for chordoma are at high risk for adverse QOL outcomes. Additionally, although nearly half of the participants reported a FCR, very few reported having adequate emotional/cognitive care. These findings may be useful in identifying specific groups of chordoma survivors vulnerable to QOL challenges and bring to light the need to expand care to meet the QOL needs for these patients.
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Cordoma , Qualidade de Vida , Humanos , Cordoma/psicologia , Cordoma/cirurgia , Qualidade de Vida/psicologia , Feminino , Masculino , Pessoa de Meia-Idade , Adulto , Idoso , Sobreviventes de Câncer/psicologia , Sobrevivência , Inquéritos e Questionários , Adulto Jovem , Adolescente , Idoso de 80 Anos ou maisRESUMO
Spinal metastasis is exceedingly common in patients with cancer and its prevalence is expected to increase. Surgical management of symptomatic spinal metastasis is indicated for pain relief, preservation or restoration of neurologic function, and mechanical stability. The overall prognosis is a major driver of treatment decisions; however, clinicians' ability to accurately predict survival is limited. In this narrative review, we first discuss the NOMS decision framework used to guide decision making in the treatment of patients with spinal metastasis. Given that decision making hinges on prognosis, multiple scoring systems have been developed over the last three decades to predict survival in patients with spinal metastasis; these systems have largely been developed using expert opinions or regression modeling. Although these tools have provided significant advances in our ability to predict prognosis, their utility is limited by the relative lack of patient-specific survival probability. Machine learning models have been developed in recent years to close this gap. Employing a greater number of features compared to models developed with conventional statistics, machine learning algorithms have been reported to predict 30-day, 6-week, 90-day, and 1-year mortality in spinal metastatic disease with excellent discrimination. These models are well calibrated and have been externally validated with domestic and international independent cohorts. Despite hypothesized and realized limitations, the role of machine learning methodology in predicting outcomes in spinal metastatic disease is likely to grow.
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STUDY DESIGN: Retrospective study. OBJECTIVE: The objective is to report the clinical data for patients treated with mobile spine chondrosarcoma. SUMMARY OF BACKGROUND DATA: Chondrosarcoma of the mobile spine is a rare and challenging entity. A handful of case series have been published that report the clinical results of treatment, largely influenced by chondrosarcoma of the appendicular skeleton and pelvis. The clinical results of patients treated for chondrosarcoma of the mobile spine from our institution were published over ten years ago and this represents and update since that publication. METHODS: Inclusion criteria were adults patients treated for chondrosarcoma of the mobile spine at Massachusetts General Hospital between 2007-2020. Patients with large sacral tumors extending into the lumbar spine were excluded. Further, we excluded patients with metastatic chondrosarcoma undergoing palliative decompressions for neurologic instability or instrumented procedures for biomechanical instability. Therefore, only patients undergoing definitive surgery at the primary site of disease in the mobile spine were included. RESULTS: Twenty-four patients were included for review in this series. Seventeen of the 24 patients had their tumors excised with negative (R0) margins. Three of these 17 patients (18%) were dead of disease at final follow-up. There were two patients with R1 resections and five patients with R2 resections. Three of the 7 patients (43%) with positive margins were dead of disease at final follow-up. A Cox proportional hazard analysis indicated total radiation dose was a significant covariate (HR 1.18, 95% CI 1.01 - 1.39, P=0.03). CONCLUSION: We found higher percentages of overall survival with R0 tumor resection and lower histologic grade whereas development of metastatic disease was closely associated with local recurrence and poor survival. Despite the improvements in treatment paradigms, it is sobering that our findings largely mirror those of previous work considering patients treated between 1984 and 2006.
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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.
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SUMMARY OF BACKGROUND DATA: The SORG-ML algorithms for survival in spinal metastatic disease were developed in patients who underwent surgery and were externally validated for patients managed operatively. OBJECTIVE: To externally validate the SORG-ML algorithms for survival in spinal metastatic disease in patients managed nonoperatively with radiation. STUDY DESIGN: Retrospective cohort. METHODS: The performance of the SORG-ML algorithms was assessed by discrimination [receiver operating curves and area under the receiver operating curve (AUC)], calibration (calibration plots), decision curve analysis, and overall performance (Brier score). The primary outcomes were 90-day and 1-year mortality. RESULTS: Overall, 2074 adult patients underwent radiation for spinal metastatic disease and 29% (n=521) and 59% (n=917) had 90-day and 1-year mortality, respectively. On complete case analysis (n=415), the AUC was 0.76 (95% CI: 0.71-0.80) and 0.78 (95% CI: 0.73-0.83) for 90-day and 1-year mortality with fair calibration and positive net benefit confirmed by the decision curve analysis. With multiple imputation (n=2074), the AUC was 0.85 (95% CI: 0.83-0.87) and 0.87 (95% CI: 0.85-0.89) for 90-day and 1-year mortality with fair calibration and positive net benefit confirmed by the decision curve analysis. CONCLUSION: The SORG-ML algorithms for survival in spinal metastatic disease generalize well to patients managed nonoperatively with radiation.
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Algoritmos , Neoplasias da Coluna Vertebral , Humanos , Masculino , Feminino , Neoplasias da Coluna Vertebral/secundário , Neoplasias da Coluna Vertebral/radioterapia , Pessoa de Meia-Idade , Idoso , Curva ROC , Análise de Sobrevida , Estudos Retrospectivos , Adulto , Área Sob a CurvaRESUMO
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.
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Fraturas por Compressão , Mieloma Múltiplo , Fraturas da Coluna Vertebral , Humanos , Masculino , Feminino , Fraturas da Coluna Vertebral/diagnóstico por imagem , Fraturas da Coluna Vertebral/epidemiologia , Fraturas da Coluna Vertebral/etiologia , Fraturas por Compressão/diagnóstico por imagem , Fraturas por Compressão/epidemiologia , Fraturas por Compressão/etiologia , Mieloma Múltiplo/epidemiologia , Mieloma Múltiplo/radioterapia , Mieloma Múltiplo/complicações , Estudos de Coortes , Qualidade de Vida , Coluna Vertebral , Estudos RetrospectivosRESUMO
BACKGROUND: Geographically based social determinants of health (SDoH) measures are useful in research and policy aimed at addressing health disparities. In the United States, the Area Deprivation Index (ADI), Neighborhood Stress Score (NSS), and Social Vulnerability Index (SVI) are frequently used, but often without a clear reason as to why one is chosen over another. There is limited evidence about how strongly correlated these geographically based SDoH measures are with one another. Further, there is a paucity of research examining their relationship with patient-reported outcome measures (PROMs) in orthopaedic patients. Such insights are important in order to determine whether comparisons of policies and care programs using different geographically based SDoH indices to address health disparities in orthopaedic surgery are appropriate. QUESTIONS/PURPOSES: Among new patients seeking care at an orthopaedic surgery clinic, (1) what is the correlation of the NSS, ADI, and SVI with one another? (2) What is the correlation of Patient-Reported Outcomes Measurement Information System (PROMIS) Global-10 physical and mental health scores and the NSS, ADI, and SVI? (3) Which geographically based SDoH index or indices are associated with presenting PROMIS Global-10 physical and mental health scores when accounting for common patient-level sociodemographic factors? METHODS: New adult orthopaedic patient encounters at clinic sites affiliated with a tertiary referral academic medical center between 2016 and 2021 were identified, and the ADI, NSS, and SVI were determined. Patients also completed the PROMIS Global-10 questionnaire as part of routine care. Overall, a total of 75,335 new patient visits were noted. Of these, 62% (46,966 of 75,335) of new patient visits were excluded because of missing PROMIS Global-10 physical and mental health scores. An additional 2.2% of patients (1685 of 75,335) were excluded because they were missing at least one SDoH index at the time of their visit (for example, if a patient only had a Post Office box listed, the SDoH index could not be determined). This left 35% of the eligible new patient visits (26,684 of 75,335) in our final sample. Though only 35% of possible new patient visits were included, the diversity of these individuals across numerous characteristics and the wide range of sociodemographic status-as measured by the SDoH indices-among included patients supports the generalizability of our sample. The mean age of patients in our sample was 55 ± 18 years and a slight majority were women (54% [14,366 of 26,684]). Among the sample, 16% (4381of 26,684) of patients were of non-White race. The mean PROMIS Global-10 physical and mental health scores were 43.4 ± 9.4 and 49.7 ± 10.1, respectively. Spearman correlation coefficients were calculated among the three SDoH indices and between each SDoH index and PROMIS Global-10 physical and mental health scores. In addition, regression analysis was used to assess the association of each SDoH index with presenting functional and mental health, accounting for key patient characteristics. The strength of the association between each SDoH index and PROMIS Global-10 physical and mental health scores was determined using partial r-squared values. Significance was set at p < 0.05. RESULTS: There was a poor correlation between the ADI and the NSS (ρ = 0.34; p < 0.001). There were good correlations between the ADI and SVI (ρ = 0.43; p < 0.001) and between the NSS and SVI (ρ = 0.59; p < 0.001). There was a poor correlation between the PROMIS Global-10 physical health and NSS (ρ = -0.14; p < 0.001), ADI (ρ = -0.24; p < 0.001), and SVI (ρ = -0.17; p < 0.001). There was a poor correlation between PROMIS Global-10 mental health and NSS (ρ = -0.13; p < 0.001), ADI (ρ = -0.22; p < 0.001), and SVI (ρ = -0.17; p < 0.001). When accounting for key sociodemographic factors, the ADI demonstrated the largest association with presenting physical health (regression coefficient: -0.13 [95% CI -0.14 to -0.12]; p < 0.001) and mental health (regression coefficient: -0.13 [95% CI -0.14 to -0.12]; p < 0.001), as confirmed by the partial r-squared values for each SDoH index (physical health: ADI 0.04 versus SVI 0.02 versus NSS 0.01; mental health: ADI 0.04 versus SVI 0.02 versus NSS 0.01). This finding means that as social deprivation increases, physical and mental health scores decrease, representing poorer health. For further context, an increase in ADI score by approximately 36 and 39 suggests a clinically meaningful (determined using distribution-based minimum clinically important difference estimates of one-half SD of each PROMIS score) worsening of physical and mental health, respectively. CONCLUSION: Orthopaedic surgeons, policy makers, and other stakeholders looking to address SDoH factors to help alleviate disparities in musculoskeletal care should try to avoid interchanging the ADI, SVI, and NSS. Because the ADI has the largest association between any of the geographically based SDoH indices and presenting physical and mental health, it may allow for easier clinical and policy application. CLINICAL RELEVANCE: We suggest using the ADI as the geographically based SDoH index in orthopaedic surgery in the United States. Further, we caution against comparing findings in one study that use one geographically based SDoH index to another study's findings that incorporates another geographically based SDoH index. Although the general findings may be the same, the strength of association and clinical relevance could differ and have policy ramifications that are not otherwise appreciated; however, the degree to which this may be true is an area for future inquiry.
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Procedimentos Ortopédicos , Ortopedia , Adulto , Humanos , Masculino , Feminino , Pessoa de Meia-Idade , Idoso , Saúde Mental , Determinantes Sociais da Saúde , Exame Físico , Medidas de Resultados Relatados pelo PacienteRESUMO
Despite the risk of complications, high dose radiation therapy is increasingly utilized in the management of selected bone malignancies. In this study, we investigate the impact of moderate to high dose radiation (over 50 Gy) on bone metabolism and structure. Between 2015 and 2018, patients with a primary malignant bone tumor of the sacrum that were either treated with high dose definitive radiation only or a combination of moderate to high dose radiation and surgery were prospectively enrolled at a single institution. Quantitative CTs were performed before and after radiation to determine changes in volumetric bone mineral density (BMD) of the irradiated and non-irradiated spine. Bone histomorphometry was performed on biopsies of the irradiated sacrum and the non-irradiated iliac crest of surgical patients using a quadruple tetracycline labeling protocol. In total, 9 patients were enrolled. Two patients received radiation only (median dose 78.3 Gy) and 7 patients received a combination of preoperative radiation (median dose 50.4 Gy), followed by surgery. Volumetric BMD of the non-irradiated lumbar spine did not change significantly after radiation, while the BMD of the irradiated sacrum did (pre-radiation median: 108.0 mg/cm3 (IQR 91.8-167.1); post-radiation median: 75.3 mg/cm3 (IQR 57.1-110.2); p = 0.010). The cancellous bone of the non-irradiated iliac crest had a stable bone formation rate, while the irradiated sacrum showed a significant decrease in bone formation rate [pre-radiation median: 0.005 mm3/mm2/year (IQR 0.003-0.009), post-radiation median: 0.001 mm3/mm2/year (IQR 0.001-0.001); p = 0.043]. Similar effects were seen in the cancellous and endocortical envelopes. This pilot study shows a decrease of volumetric BMD and bone formation rate after high-dose radiation therapy. Further studies with larger cohorts and other endpoints are needed to get more insight into the effect of radiation on bone. Level of evidence: IV.
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Densidade Óssea , Sacro , Humanos , Projetos Piloto , Sacro/cirurgia , Vértebras Lombares , ÍlioRESUMO
BACKGROUND: Preoperative prediction of prolonged postoperative opioid use (PPOU) after total knee arthroplasty (TKA) could identify high-risk patients for increased surveillance. The Skeletal Oncology Research Group machine learning algorithm (SORG-MLA) has been tested internally while lacking external support to assess its generalizability. The aims of this study were to externally validate this algorithm in an Asian cohort and to identify other potential independent factors for PPOU. METHODS: In a tertiary center in Taiwan, 3,495 patients receiving TKA from 2010-2018 were included. Baseline characteristics were compared between the external validation cohort and the original developmental cohorts. Discrimination (area under receiver operating characteristic curve [AUROC] and precision-recall curve [AUPRC]), calibration, overall performance (Brier score), and decision curve analysis (DCA) were applied to assess the model performance. A multivariable logistic regression was used to evaluate other potential prognostic factors. RESULTS: There were notable differences in baseline characteristics between the validation and the development cohort. Despite these variations, the SORG-MLA ( https://sorg-apps.shinyapps.io/tjaopioid/ ) remained its good discriminatory ability (AUROC, 0.75; AUPRC, 0.34) and good overall performance (Brier score, 0.029; null model Brier score, 0.032). The algorithm could bring clinical benefit in DCA while somewhat overestimating the probability of prolonged opioid use. Preoperative acetaminophen use was an independent factor to predict PPOU (odds ratio, 2.05). CONCLUSIONS: The SORG-MLA retained its discriminatory ability and good overall performance despite the different pharmaceutical regulations. The algorithm could be used to identify high-risk patients and tailor personalized prevention policy.
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Artroplastia do Joelho , Transtornos Relacionados ao Uso de Opioides , Humanos , Analgésicos Opioides/efeitos adversos , Artroplastia do Joelho/efeitos adversos , Aprendizado de Máquina , Algoritmos , Prescrições , Estudos RetrospectivosRESUMO
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: The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA) was developed to predict the survival of patients with spinal metastasis. The algorithm was successfully tested in five international institutions using 1101 patients from different continents. The incorporation of 18 prognostic factors strengthens its predictive ability but limits its clinical utility because some prognostic factors might not be clinically available when a clinician wishes to make a prediction. QUESTIONS/PURPOSES: We performed this study to (1) evaluate the SORG-MLA's performance with data and (2) develop an internet-based application to impute the missing data. METHODS: A total of 2768 patients were included in this study. The data of 617 patients who were treated surgically were intentionally erased, and the data of the other 2151 patients who were treated with radiotherapy and medical treatment were used to impute the artificially missing data. Compared with those who were treated nonsurgically, patients undergoing surgery were younger (median 59 years [IQR 51 to 67 years] versus median 62 years [IQR 53 to 71 years]) and had a higher proportion of patients with at least three spinal metastatic levels (77% [474 of 617] versus 72% [1547 of 2151]), more neurologic deficit (normal American Spinal Injury Association [E] 68% [301 of 443] versus 79% [1227 of 1561]), higher BMI (23 kg/m2 [IQR 20 to 25 kg/m2] versus 22 kg/m2 [IQR 20 to 25 kg/m2]), higher platelet count (240 × 103/µL [IQR 173 to 327 × 103/µL] versus 227 × 103/µL [IQR 165 to 302 × 103/µL], higher lymphocyte count (15 × 103/µL [IQR 9 to 21× 103/µL] versus 14 × 103/µL [IQR 8 to 21 × 103/µL]), lower serum creatinine level (0.7 mg/dL [IQR 0.6 to 0.9 mg/dL] versus 0.8 mg/dL [IQR 0.6 to 1.0 mg/dL]), less previous systemic therapy (19% [115 of 617] versus 24% [526 of 2151]), fewer Charlson comorbidities other than cancer (28% [170 of 617] versus 36% [770 of 2151]), and longer median survival. The two patient groups did not differ in other regards. These findings aligned with our institutional philosophy of selecting patients for surgical intervention based on their level of favorable prognostic factors such as BMI or lymphocyte counts and lower levels of unfavorable prognostic factors such as white blood cell counts or serum creatinine level, as well as the degree of spinal instability and severity of neurologic deficits. This approach aims to identify patients with better survival outcomes and prioritize their surgical intervention accordingly. Seven factors (serum albumin and alkaline phosphatase levels, international normalized ratio, lymphocyte and neutrophil counts, and the presence of visceral or brain metastases) were considered possible missing items based on five previous validation studies and clinical experience. Artificially missing data were imputed using the missForest imputation technique, which was previously applied and successfully tested to fit the SORG-MLA in validation studies. Discrimination, calibration, overall performance, and decision curve analysis were applied to evaluate the SORG-MLA's performance. The discrimination ability was measured with an area under the receiver operating characteristic curve. It ranges from 0.5 to 1.0, with 0.5 indicating the worst discrimination and 1.0 indicating perfect discrimination. An area under the curve of 0.7 is considered clinically acceptable discrimination. Calibration refers to the agreement between the predicted outcomes and actual outcomes. An ideal calibration model will yield predicted survival rates that are congruent with the observed survival rates. The Brier score measures the squared difference between the actual outcome and predicted probability, which captures calibration and discrimination ability simultaneously. A Brier score of 0 indicates perfect prediction, whereas a Brier score of 1 indicates the poorest prediction. A decision curve analysis was performed for the 6-week, 90-day, and 1-year prediction models to evaluate their net benefit across different threshold probabilities. Using the results from our analysis, we developed an internet-based application that facilitates real-time data imputation for clinical decision-making at the point of care. This tool allows healthcare professionals to efficiently and effectively address missing data, ensuring that patient care remains optimal at all times. RESULTS: Generally, the SORG-MLA demonstrated good discriminatory ability, with areas under the curve greater than 0.7 in most cases, and good overall performance, with up to 25% improvement in Brier scores in the presence of one to three missing items. The only exceptions were albumin level and lymphocyte count, because the SORG-MLA's performance was reduced when these two items were missing, indicating that the SORG-MLA might be unreliable without these values. The model tended to underestimate the patient survival rate. As the number of missing items increased, the model's discriminatory ability was progressively impaired, and a marked underestimation of patient survival rates was observed. Specifically, when three items were missing, the number of actual survivors was up to 1.3 times greater than the number of expected survivors, while only 10% discrepancy was observed when only one item was missing. When either two or three items were omitted, the decision curves exhibited substantial overlap, indicating a lack of consistent disparities in performance. This finding suggests that the SORG-MLA consistently generates accurate predictions, regardless of the two or three items that are omitted. We developed an internet application (https://sorg-spine-mets-missing-data-imputation.azurewebsites.net/) that allows the use of SORG-MLA with up to three missing items. CONCLUSION: The SORG-MLA generally performed well in the presence of one to three missing items, except for serum albumin level and lymphocyte count (which are essential for adequate predictions, even using our modified version of the SORG-MLA). We recommend that future studies should develop prediction models that allow for their use when there are missing data, or provide a means to impute those missing data, because some data are not available at the time a clinical decision must be made. CLINICAL RELEVANCE: The results suggested the algorithm could be helpful when a radiologic evaluation owing to a lengthy waiting period cannot be performed in time, especially in situations when an early operation could be beneficial. It could help orthopaedic surgeons to decide whether to intervene palliatively or extensively, even when the surgical indication is clear.
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BACKGROUND: Survival is an important factor to consider when clinicians make treatment decisions for patients with skeletal metastasis. Several preoperative scoring systems (PSSs) have been developed to aid in survival prediction. Although we previously validated the Skeletal Oncology Research Group Machine-learning Algorithm (SORG-MLA) in Taiwanese patients of Han Chinese descent, the performance of other existing PSSs remains largely unknown outside their respective development cohorts. We aim to determine which PSS performs best in this unique population and provide a direct comparison between these models. METHODS: We retrospectively included 356 patients undergoing surgical treatment for extremity metastasis at a tertiary center in Taiwan to validate and compare eight PSSs. Discrimination (c-index), decision curve (DCA), calibration (ratio of observed:expected survivors), and overall performance (Brier score) analyses were conducted to evaluate these models' performance in our cohort. RESULTS: The discriminatory ability of all PSSs declined in our Taiwanese cohort compared with their Western validations. SORG-MLA is the only PSS that still demonstrated excellent discrimination (c-indexes>0.8) in our patients. SORG-MLA also brought the most net benefit across a wide range of risk probabilities on DCA with its 3-month and 12-month survival predictions. CONCLUSIONS: Clinicians should consider potential ethnogeographic variations of a PSS's performance when applying it onto their specific patient populations. Further international validation studies are needed to ensure that existing PSSs are generalizable and can be integrated into the shared treatment decision-making process. As cancer treatment keeps advancing, researchers developing a new prediction model or refining an existing one could potentially improve their algorithm's performance by using data gathered from more recent patients that are reflective of the current state of cancer care.
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Algoritmos , Extremidades , Humanos , Prognóstico , Estudos Retrospectivos , Taiwan/epidemiologiaRESUMO
PURPOSE: Effects of clockwise torque rotation onto proximal femoral fracture fixation have been subject of ongoing debate: fixated right-sided trochanteric fractures seem more rotationally stable than left-sided fractures in the biomechanical setting, but this theoretical advantage has not been demonstrated in the clinical setting to date. The purpose of this study was to identify a difference in early reoperation rate between patients undergoing surgery for left- versus right-sided proximal femur fractures using cephalomedullary nailing (CMN). MATERIALS AND METHODS: The American College of Surgeons National Surgical Quality Improvement Program was queried from 2016-2019 to identify patients aged 50 years and older undergoing CMN for a proximal femoral fracture. The primary outcome was any unplanned reoperation within 30 days following surgery. The difference was calculated using a Chi-square test, and observed power calculated using post-hoc power analysis. RESULTS: In total, of 20,122 patients undergoing CMN for proximal femoral fracture management, 1.8% (n=371) had to undergo an unplanned reoperation within 30 days after surgery. Overall, 208 (2.0%) were left-sided and 163 (1.7%) right-sided fractures (p=0.052, risk ratio [RR] 1.22, 95% confidence interval [CI] 1.00-1.50), odds ratio [OR] 1.23 (95%CI 1.00-1.51), power 49.2% (α=0.05). CONCLUSION: This study shows a higher risk of reoperation for left-sided compared to right-sided proximal femur fractures after CMN in a large sample size. Although results may be underpowered and statistically insignificant, this finding might substantiate the hypothesis that clockwise rotation during implant insertion and (postoperative) weightbearing may lead to higher reoperation rates. LEVEL OF EVIDENCE: Therapeutic level II.
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Fraturas do Fêmur , Fixação Intramedular de Fraturas , Fraturas do Quadril , Fraturas Proximais do Fêmur , Humanos , Pessoa de Meia-Idade , Idoso , Reoperação , Torque , Pinos Ortopédicos , Resultado do Tratamento , Fraturas do Fêmur/cirurgia , Fraturas do Quadril/cirurgia , Fêmur , Estudos RetrospectivosRESUMO
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.