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Limited health literacy has previously been associated with increased healthcare utilization, worse general health status and self-reported health, and increased mortality. Identifying and accommodating patients with limited health literacy may offer an avenue towards mitigating adverse health outcomes and reduce unnecessary healthcare expenditure. Due to the challenges associated with implementation of lengthy health literacy assessments, the Brief Health Literacy Screening Instrument was developed. However, to our knowledge, there are no reports on the accuracy of this screening questionnaire, with or without the inclusion of sociodemographic characteristics, when predicting limited health literacy in orthopaedic spine patients.To evaluate the reliability and predictive accuracy of self-reported health literacy screening questions with and without the inclusion of sociodemographic variables in orthopaedic spine patients.Cross-sectional PATIENT SAMPLE: Patients seen at a tertiary urban academic hospital-based multi-surgeon spine center OUTCOME MEASURES: Brief Health Literacy Screening Instrument (BRIEF), and the Newest Vital Sign (NVS) health literacy assessment tool.Between December 2021 and February 2022, consecutive English-speaking patients over the age of 18 presenting as new patients to an urban, hospital-based outpatient spine clinic were approached for participation. A sociodemographic survey, the Brief Health Literacy Screening Instrument (BRIEF), and the Newest Vital Sign (NVS) Health Literacy Assessment Tool were administered verbally. Simple and multivariable logistic regression were utilized to assess the accuracy of each BRIEF question individually, and collectively, at predicting limited health literacy as defined by the NVS. Further regression analysis included sociodemographic variables (age, body mass index, race, ethnicity, highest educational degree, employment status, marital status, annual household income, insurance status, and self-reported health.A total of 262 patients [mean age (years), 57 ± 17] were included in this study. One hundred thirty-four (51%) were male, 223 (85%) were White, and 151 (58%) were married. Patient BRIEF scores were as follows: 23 (9%) limited, 43 (16%) marginal, and 196 (75%) adequate. NVS scores identified 87 (33%) patients with possible limited health literacy. BRIEF items collectively demonstrated fair accuracy in the prediction of limited health literacy (AUROC, 0.76; 95% CI, 0.70-0.82). Individually, the fourth BRIEF item ("How confident are you in filling out medical forms by yourself?") was the best predictor of limited health literacy (AUROC, 0.67; 95% CI, 0.60-0.73). The predictive accuracy of the BRIEF items, both individually and collectively, increased with the inclusion of sociodemographic variables within the logistic regression. Specific characteristics independently associated with limited health literacy were self-identified Black race, retired or disabled employment status, single or divorced marital status, high school education or below, and self-reported "poor" health.Limited health literacy has implications for patient outcomes and healthcare costs. Our results show that the BRIEF questionnaire is a low-cost screening tool that demonstrates fair predictability in determining limited health literacy within a population of spine patients. Self-reported health literacy assessments may be more feasible in daily practice and easier to implement into clinical workflow.

AimsTo develop prediction models using machine-learning (ML) algorithms for 90-day and one-year mortality prediction in femoral neck fracture (FNF) patients aged 50 years or older based on the Hip fracture Evaluation with Alternatives of Total Hip arthroplasty versus Hemiarthroplasty (HEALTH) and Fixation using Alternative Implants for the Treatment of Hip fractures (FAITH) trials.MethodsThis study included 2,388 patients from the HEALTH and FAITH trials, with 90-day and one-year mortality proportions of 3.0% (71/2,388) and 6.4% (153/2,388), respectively. The mean age was 75.9 years (SD 10.8) and 65.9% of patients (1,574/2,388) were female. The algorithms included patient and injury characteristics. Six algorithms were developed, internally validated and evaluated across discrimination (c-statistic; discriminative ability between those with risk of mortality and those without), calibration (observed outcome compared to the predicted probability), and the Brier score (composite of discrimination and calibration).ResultsThe developed algorithms distinguished between patients at high and low risk for 90-day and one-year mortality. The penalized logistic regression algorithm had the best performance metrics for both 90-day (c-statistic 0.80, calibration slope 0.95, calibration intercept -0.06, and Brier score 0.039) and one-year (c-statistic 0.76, calibration slope 0.86, calibration intercept -0.20, and Brier score 0.074) mortality prediction in the hold-out set.ConclusionUsing high-quality data, the ML-based prediction models accurately predicted 90-day and one-year mortality in patients aged 50 years or older with a FNF. The final models must be externally validated to assess generalizability to other populations, and prospectively evaluated in the process of shared decision-making.Cite this article: Bone Jt Open 2023;4(3):168–181.

Local control remains a vexing problem in the management of chordoma despite advances in operative techniques and radiotherapy (RT) protocols. Existing studies show satisfactory local control rates with different treatment modalities. However, those studies with minimum follow-up more than 4 years demonstrate increasing rates of local failure. Therefore, mid-term local survival rates may be inadvertently elevated by studies with less than 4 years follow-up.The purpose of this study is to report the mid-term results of primary spinal chordoma treated with en bloc resection and proton-based RT with minimum 5 years of follow-up.Retrospective, single-center, cohort study.Patients undergoing primary surgical excision of a spine or sacral chordoma tumor between 1990 and 2016 at a single-institution were included. Patients were included if they had a local failure at any time, or they had a minimum of 5 years of follow up with no local failure. Patients were excluded if a prior surgical excision was performed or metastases were present at the time of referral.The outcome measures were local recurrence-free interval (LRFI) and overall survival (OS).Demographic, clinical, oncologic and surgical variables, including margin status, as well as radiation doses and schedule (neoadjuvant, adjuvant, or both) were compared using Wilcoxon rank-sum or chi-squared testing. The goal RT dose was 70 Gray (total) and patients were stratified based on completing (C70) or receiving incomplete (I70) dosing. Overall survival (OS) and local-recurrence free interval (LRFI) were calculated using the Kaplan-Meier method.No funding was obtained for this work.Seventy-six patients were included in the final analysis. All patients had a minimum of 5-year follow-up (median 9.3 years, range 5.1-24.7 years). There were no significant clinical differences between the C70 and I70 RT groups. OS was greater for the C70 RT group (5-year OS 82% vs. 63%, p=.001). There was similar OS for the positive margin group (5-year OS 70% vs. 61%, p=.266). LRFI was greater for the C70 RT group (5-year OS 93% vs. 78%, p=.017). There was similar LRFI for the positive margin group (5-year OS 90% versus 87%, p=.810).Chordoma outcomes trend towards diminishing LRFI rates in the literature. Here we report the results of the operative management of primary spinal chordoma with minimum five year follow-up, the addition of C70 RT to surgical excision conferred a benefit to OS and local recurrence.

Historically, spine surgeons used expected postoperative survival of 3-months to help select candidates for operative intervention in spinal metastasis. However, this cutoff has been challenged by the development of minimally invasive techniques, novel biologics, and advanced radiotherapy. Recent studies have suggested that a life expectancy of 6 weeks may be enough to achieve significant improvements in postoperative health-related quality of life.The purpose of this study was to develop a model capable of predicting 6-week mortality in patients with spinal metastases treated with radiation or surgery.A retrospective review was conducted at five large tertiary centers in the United States and Taiwan.The development cohort consisted of 3,001 patients undergoing radiotherapy and/or surgery for spinal metastases from one institution. The validation institutional cohort consisted of 1,303 patients from four independent, external institutions.The primary outcome was 6-week mortality.Five models were considered to predict 6-week mortality, and the model with the best performance across discrimination, calibration, decision-curve analysis, and overall performance was integrated into an open access web-based application.The most important variables for prediction of 6-week mortality were albumin, primary tumor histology, absolute lymphocyte, three or more spine metastasis, and ECOG score. The elastic-net penalized logistic model was chosen as the best performing model with AUC 0.84 on evaluation in the independent testing set. On external validation in the 1,303 patients from the four independent institutions, the model retained good discriminative ability with an area under the curve of 0.81. The model is available here: https://sorg-apps.shinyapps.io/spinemetssurvival/.While this study does not advocate for the use of a 6-week life expectancy as criteria for considering operative management, the algorithm developed and externally validated in this study may be helpful for preoperative planning, multidisciplinary management, and shared decision-making in spinal metastasis patients with shorter life expectancy.

Spinal epidural abscess is a rare but severe condition with high rates of postoperative adverse events.The objective of the study was to identify independent prognostic factors for reoperation using two datasets: an institutional and national database.Retrospective Review.Database 1: Review of five medical centers from 1993 to 2016. Database 2: The National Surgical Quality Improvement Program (NSQIP) was queried between 2012 and 2016.Thirty-day and ninety-day reoperation rate.Two independent datasets were reviewed to identify patients with spinal epidural abscesses undergoing spinal surgery. Multivariate analyses were used to determine independent prognostic factors for reoperation while including factors identified in bivariate analyses.Overall, 642 patients underwent surgery for a spinal epidural abscess in the institutional cohort, with a 90-day unplanned reoperation rate of 19.9%. In the NSQIP database, 951 patients were identified with a 30-day unplanned reoperation rate of 12.3%. On multivariate analysis in the NSQIP database, cervical spine abscess was the only factor that reached significance for 30-day reoperation (OR=1.71, 95% CI=1.11-2.63, p=.02, Area under the curve (AUC)=0.61). On multivariate analysis in the institutional cohort, independent prognostic factors for 30-day reoperation were: preoperative urinary incontinence, ventral location of abscess relative to thecal sac, cervical abscess, preoperative wound infection, and leukocytosis (AUC=0.65). Ninety-day reoperation rate also found hypoalbuminemia as a significant predictor (AUC=0.66).Six novel independent prognostic factors were identified for 90-day reoperation after surgery for a spinal epidural abscess. The multivariable analysis fairly predicts reoperation, indicating that there may be additional factors that need to be uncovered in future studies. The risk factors delineated in this study through the use of two large cohorts of spinal epidural abscess patients can be used to improve preoperative risk stratification and patient management.

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).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.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.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.

Cross-sectional survey study.To determine if health literacy level is associated with patient-reported outcomes and self-reported health status among patients presenting to an academic outpatient spine center.Patient reports are critical to assessing symptom severity and treatment success in orthopaedic spine patients. Patient-reported outcome measures (PROMs) are important instruments commonly used for this purpose. However, the influence of patient health literacy on PROMs has not yet been given much consideration in spine literature.Consecutive English-speaking patients over the age of 18 years and new to our clinic verbally completed the Newest Vital Sign health literacy assessment tool and a sociodemographic survey, including self-reported health status. Additionally, seven Patient-Reported Outcomes Measurement Information System scores were extracted from patient records. Regression modeling was performed with PROMs considered as dependent variables, health literacy level as the primary predictor, and all other factors (age, sex, race, ethnicity, native English speaker, highest educational degree, grade-level reading, marital status, employment status, annual household income and type of insurance) as covariates.Among the 318 included patients, 33% had limited health literacy. Adjusted regression analysis demonstrated that patients with limited health literacy had worse PROM scores across all seven domains (Physical Function: P=0.028; Depression: P=0.035; Global Health - Physical: P=0.001; Global Health - Mental: P=0.007; Pain Interference: P=0.036; Pain Intensity: P=0.002; Anxiety: P=0.047). Additionally, patients with limited health literacy reported worse self-reported health status (P=0.001).Spine patients with limited health literacy have worse baseline PROM scores confounders and report worse general health. Further investigations are necessary to elucidate if limited health literacy is a marker or the root cause of these disparities. Findings from this study urge the consideration of patient health literacy when interpreting PROMs as well as the implications for patient assessment and discussion of treatment options.

Background Incidental durotomy is an intraoperative complication in spine surgery that can lead to postoperative complications, increased length of stay, and higher healthcare costs. Natural language processing (NLP) is an artificial intelligence method that assists in understanding free-text notes that may be useful in the automated surveillance of adverse events in orthopaedic surgery. A previously developed NLP algorithm is highly accurate in the detection of incidental durotomy on internal validation and external validation in an independent cohort from the same country. External validation in a cohort with linguistic differences is required to assess the transportability of the developed algorithm, referred to geographical validation. Ideally, the performance of a prediction model, the NLP algorithm, is constant across geographic regions to ensure reproducibility and model validity.Question/purpose Can we geographically validate an NLP algorithm for the automated detection of incidental durotomy across three independent cohorts from two continents?Methods Patients 18 years or older undergoing a primary procedure of (thoraco)lumbar spine surgery were included. In Massachusetts, between January 2000 and June 2018, 1000 patients were included from two academic and three community medical centers. In Maryland, between July 2016 and November 2018, 1279 patients were included from one academic center, and in Australia, between January 2010 and December 2019, 944 patients were included from one academic center. The authors retrospectively studied the free-text operative notes of included patients for the primary outcome that was defined as intraoperative durotomy. Incidental durotomy occurred in 9% (93 of 1000), 8% (108 of 1279), and 6% (58 of 944) of the patients, respectively, in the Massachusetts, Maryland, and Australia cohorts. No missing reports were observed. Three datasets (Massachusetts, Australian, and combined Massachusetts and Australian) were divided into training and holdout test sets in an 80:20 ratio. An extreme gradient boosting (an efficient and flexible tree-based algorithm) NLP algorithm was individually trained on each training set, and the performance of the three NLP algorithms (respectively American, Australian, and combined) was assessed by discrimination via area under the receiver operating characteristic curves (AUC-ROC; this measures the model's ability to distinguish patients who obtained the outcomes from those who did not), calibration metrics (which plot the predicted and the observed probabilities) and Brier score (a composite of discrimination and calibration). In addition, the sensitivity (true positives, recall), specificity (true negatives), positive predictive value (also known as precision), negative predictive value, Fl-score (composite of precision and recall), positive likelihood ratio, and negative likelihood ratio were calculated.Results The combined NLP algorithm (the combined Massachusetts and Australian data) achieved excellent performance on independent testing data from Australia (AUC-ROC 0.97 [95% confidence interval 0.87 to 0.99]), Massachusetts (AUC-ROC 0.99 [95% CI 0.80 to 0.99]) and Maryland (AUC-ROC 0.95 [95% CI 0.93 to 0.97]). The NLP developed based on the Massachusetts cohort had excellent performance in the Maryland cohort (AUC-ROC 0.97 [95% CI 0.95 to 0.99]) but worse performance in the Australian cohort (AUC-ROC 0.74 [95% CI 0.70 to 0.77]).Conclusion We demonstrated the clinical utility and reproducibility of an NLP algorithm with combined datasets retaining excellent performance in individual countries relative to algorithms developed in the same country alone for detection of incidental durotomy. Further multi-institutional, international collaborations can facilitate the creation of universal NLP algorithms that improve the quality and safety of orthopaedic surgery globally. The combined NLP algorithm has been incorporated into a freely accessible web application that can be found at https://sorg-apps.shinyapps.io/nlp_incidental_durotomy/. Clinicians and researchers can use the tool to help incorporate the model in evaluating spine registries or quality and safety departments to automate detection of incidental durotomy and optimize prevention efforts.

Background: Limited health literacy has been associated with adverse health outcomes. Undergoing orthopedic surgery often requires patients to make complex decisions and adhere to complicated instructions, suggesting that health literacy skills might have a profound impact on orthopedic surgery outcomes. Purpose: We sought to review the literature for studies investigating the level of health literacy in patients undergoing orthopedic surgery and also to assess how those studies report factors affecting health equity. Methods: We conducted a systematic search of PubMed, Embase, and Cochrane Library for all health literacy studies published in the orthopedic surgery literature up to February 8, 2022. Search terms included synonyms for health literacy and for all orthopedic surgery subspecialties. Two reviewers independently extracted study data in addition to indicators of equity reporting using the PROGRESS+ checklist (Place of Residence, Race/Ethnicity, Occupation, Gender/sex, Religion, Education, Social capital, Socioeconomic status, plus age, disability, and sexual orientation). Results: The search resulted in 616 studies; 9 studies remained after exclusion criteria were applied. Most studies were of arthroplasty (4/9; 44%) or trauma (3/9; 33%) patients. Validated health literacy assessments were used in 4 of the included studies, and only 3 studies reported the rate of limited health literacy in the patients studied, which ranged between 34% and 38.5%. At least one PROGRESS+ item was reported in 88% (8/9) of the studies. Conclusions: We found a paucity of appropriately designed studies that used validated measures of health literacy in the field of orthopedic surgery. The potential impact of health literacy on orthopedic patients and their outcomes has yet to be elucidated. Thoughtful, high-quality trials across diverse demographics and geographies are warranted.

Preoperative prediction of prolonged postoperative opioid prescription helps identify patients for increased surveillance after surgery. The SORG machine learning model has been developed and successfully tested using 5,413 patients from the United States (US) to predict the risk of prolonged opioid prescription after surgery for lumbar disc herniation. However, external validation is an often-overlooked element in the process of incorporating prediction models in current clinical practice. This cannot be stressed enough in prediction models where medicolegal and cultural differences may play a major role.The authors aimed to investigate the generalizability of the US citizens prediction model SORG to a Taiwanese patient cohort.Retrospective study at a large academic medical center in Taiwan.Of 1,316 patients who were 20 years or older undergoing initial operative management for lumbar disc herniation between 2010 and 2018.The primary outcome of interest was prolonged opioid prescription defined as continuing opioid prescription to at least 90 to 180 days after the first surgery for lumbar disc herniation at our institution.Baseline characteristics were compared between the external validation cohort and the original developmental cohorts. Discrimination (area under the receiver operating characteristic curve and the area under the precision-recall curve), calibration, overall performance (Brier score), and decision curve analysis were used to assess the performance of the SORG ML algorithm in the validation cohort. This study had no funding source or conflict of interests.Overall, 1,316 patients were identified with sustained postoperative opioid prescription in 41 (3.1%) patients. The validation cohort differed from the development cohort on several variables including 93% of Taiwanese patients receiving NSAIDS preoperatively compared with 22% of US citizens patients, while 30% of Taiwanese patients received opioids versus 25% in the US. Despite these differences, the SORG prediction model retained good discrimination (area under the receiver operating characteristic curve of 0.76 and the area under the precision-recall curve of 0.33) and good overall performance (Brier score of 0.028 compared with null model Brier score of 0.030) while somewhat overestimating the chance of prolonged opioid use (calibration slope of 1.07 and calibration intercept of -0.87). Decision-curve analysis showed the SORG model was suitable for clinical use.Despite differences at baseline and a very strict opioid policy, the SORG algorithm for prolonged opioid use after surgery for lumbar disc herniation has good discriminative abilities and good overall performance in a Han Chinese patient group in Taiwan. This freely available digital application can be used to identify high-risk patients and tailor prevention policies for these patients that may mitigate the long-term adverse consequence of opioid dependence: https://sorg-apps.shinyapps.io/lumbardiscopioid/.

Treatment of spine and sacral chordoma generally involves surgical resection, usually in conjunction with radiation therapy.In certain locations, resection may result in significant neurological dysfunction, so definitive radiation has been used as an alternative to surgery. The purpose of this study is to report the results of high-dose, proton-based definitive radiotherapy for unresected spinal and sacral chordomas.Retrospective review of 67 patients with newly diagnosed, unresected spinal chordomas treated with high-dose definitive, proton-based radiotherapy at our center from 1975 to 2019.Reasons for radiotherapy alone included medical inoperability and/or concern for neurological dysfunction based on spine level or patient choice. Tumor locations included cervical (n = 10), thoracic (n = 1), lumbar (n = 4) spine, and sacrum (n = 52). Median maximal tumor diameter was 7.4 cm (range 1.8-25 cm). Median total dose was 77.4 Gy (RBE) (range 73.8-85.9 Gy RBE). Analysis with median follow-up of 56.2 months (range, 4-171.7 months) showed overall survival of 83.5 % (95%CI: 69.4-91.5%) and 65.9% (95%CI: 47.3-79.3%), disease-free survival of 64% (95%CI: 49.3-75.4) and 44.1% (95%CI: 27.8-59.2%), local control of 81.8% (95%CI: 67.6-90.2%) and 63.6% (95%CI: 44.7-77.5%), and distant control of 77.4% (95%CI: 63.6-86.5%) and 72.5% (95%CI: 55.7-83.8%) at 5 and 8 years respectively. The most common late side effect was insufficiency fracture.These results continue to support the use of high-dose definitive radiotherapy for patients with medically inoperable or otherwise unresected mobile spine or sacrococcygeal chordomas. There is a trend towards better disease-free survival with doses 78 Gy (RBE).

Giant cell tumor of bone (GCTB) is a destructive lesion with a high potential for recurrence. RANK-ligand targeted therapy has provided promising, yet mixed results. Sclerostin (SOST) inhibition results in a net anabolic response and is currently used in the treatment of osteoporosis. The application to GCTB is unknown.We sought to determine if GCTB stained for SOST on immunohistochemistry and correlate its expression with predictor variables.All patients at a single institution undergoing surgery for GCTB between 1993 and 2008 with a minimum of 6 months follow-up were included. Primary outcomes included the presence of SOST staining, secondary outcomes included the correlation of patient and tumor-specific predictor variables.SOST antibody staining of any cell type was present in 47 of 48 cases (97.9%). Positivity of the stromal cells was present in 39 of 48 cases (81.3%) and was associated with radiographic aggressiveness (p = 0.023), symptomatic presentation (p = 0.032), prior surgery (p = 0.005), and patient age (p = 0.034). Positivity of giant cells was present in 41 of 48 cases (85.4%) and was not significant with predictive factors.Sclerostin staining in GCTB is a novel finding and warrants further research to define the role of sclerostin as a prognostic factor and therapeutic target.

This was a retrospective cohort study.The objective of this study was to assess variation in care for degenerative spondylolisthesis (DS) among surgeons at the same institution, to establish diagnostic and therapeutic variables contributing to this variation, and to determine whether variation in care changed over time.Like other degenerative spinal disorders, DS is prone to practice variation due to the wide array of treatment options. Focusing on a single institution can identify more individualized drivers of practice variation by omitting geographic variability of demographics and socioeconomic factors.We collected number of office visits, imaging procedures, injections, electromyography (EMG), and surgical procedures within 1 year after diagnosis. Multivariable logistic regression was used to determine predictors of surgery. The coefficient of variation (CV) was calculated to compare the variation in practice over time.Patients had a mean 2.5 (±0.6) visits, 1.8 (±0.7) imaging procedures, and 0.16 (±0.09) injections in the first year after diagnosis. Thirty-six percent (1937/5091) of patients had physical therapy in the 3 months after diagnosis. CV was highest for EMG (95%) and lowest for office visits (22%). An additional spinal diagnosis [odds ratio (OR)=3.99, P0.001], visiting a neurosurgery clinic (OR=1.81, P =0.016), and diagnosis post-2007 (OR=1.21, P =0.010) were independently associated with increased surgery rates. The CVs for all variables decreased after 2007, with the largest decrease seen for EMG (132% vs. 56%).While there is variation in the management of patients diagnosed with DS between surgeons of a single institution, this variation seems to have gone down in recent years. All practice variables showed diminished variation. The largest variation and subsequent decrease of variation was seen in the use of EMG. Despite the smaller amount of variation, the rate of surgery has gone up since 2007.

The recent impressive clinical responses to antibody-based immunotherapy have prompted the identification of clinically relevant tumor antigens that can serve as targets in solid tumors. Among them, B7-H3, a member of the B7 ligand family, represents an attractive target for antibody-based immunotherapy, it is overexpressed on differentiated malignant cells and cancer-initiating cells, with limited heterogeneity, and high frequency (60% of 25,000 tumor samples) in many different cancer types, but has a limited expression at low level in normal tissues. In nonmalignant tissues, B7-H3 has a predominantly inhibitory role in adaptive immunity, suppressing T-cell activation and proliferation. In malignant tissues, B7-H3 inhibits tumor antigen–specific immune responses, leading to a protumorigenic effect. B7-H3 also has nonimmunologic protumorigenic functions, such as promoting migration and invasion, angiogenesis, chemoresistance, and endothelial-to-mesenchymal transition, as well as affecting tumor cell metabolism. As a result, B7-H3 expression in tumors is associated with poor prognosis. Although experimental B7-H3 silencing reduces cancer cell malignant potential, there has been limited emphasis on the development of B7-H3–blocking antibodies, most likely because the B7-H3 receptor remains unknown. Instead, many antibody-based strategies utilizing distinct effector mechanisms to target B7-H3–expressing cancer cells have been developed. These strategies have demonstrated potent antitumor activity and acceptable safety profiles in preclinical models. Ongoing clinical trials are assessing their safety and efficacy in patients. Identification of the B7-H3 receptor will improve our understanding of its role in tumor immunity, and will suggest rational strategies to develop blocking antibodies, which may enhance the therapeutic efficacy of tumor immunity.

Supplemental Materials & Methods and Figures 1-6. Sup. Figure 1. The effect of antiestrogens against ER+ BrCa spheroid cultures is attenuated by BMSCs. Sup. Figure 2. BMSCs attenuate the antiestrogen response of BrCa xenografts in vivo. Sup. Figure 3. BMSCs attenuate hormone-induced gene expression in cancer spheroids with varying effect on HR expression. Sup. Figure 4. BMSCs paracrine effect induces HT resistance in PrCa/BrCa 3D spheroids via IL-6 secretion or in IL-6-independent manner. Sup. Figure 5. Transcriptional signatures of genes downregulated (log2FC< -1) or upregulated (log2FC > 1) in MCF7 spheroids cocultured (8 days) with HS5 (vs. monoculture) do not correlate with relapse-free survival of 342 ER-negative BrCa patients (stratified using the upper tertile of the respective signature as cutoff). Sup. Figure 6. BrCa spheroids in coculture with BMSC acquire increased dependence on growth factor receptor and downstream signaling.

Supplementary Tables 1-3

Although hormonal therapy (HT) inhibits the growth of hormone receptor–positive (HR+) breast and prostate cancers, HT resistance frequently develops within the complex metastatic microenvironment of the host organ (often the bone), a setting poorly recapitulated in 2D culture systems. To address this limitation, we cultured HR+ breast cancer and prostate cancer spheroids and patient-derived organoids in 3D extracellular matrices (ECM) alone or together with bone marrow stromal cells (BMSC). In 3D monocultures, antiestrogens and antiandrogens induced anoikis by abrogating anchorage-independent growth of HR+ cancer cells but exhibited only modest effects against tumor cells residing in the ECM niche. In contrast, BMSC induced hormone-independent growth of breast cancer and prostate cancer spheroids and restored lumen filling in the presence of HR-targeting agents. Molecular and functional characterization of BMSC-induced hormone independence and HT resistance in anchorage-independent cells revealed distinct context-dependent mechanisms. Cocultures of ZR75-1 and LNCaP with BMSCs exhibited paracrine IL6-induced HT resistance via attenuation of HR protein expression, which was reversed by inhibition of IL6 or JAK signaling. Paracrine IL6/JAK/STAT3-mediated HT resistance was confirmed in patient-derived organoids cocultured with BMSCs. Distinctly, MCF7 and T47D spheroids retained ER protein expression in cocultures but acquired redundant compensatory signals enabling anchorage independence via ERK and PI3K bypass cascades activated in a non–IL6-dependent manner. Collectively, these data characterize the pleiotropic hormone-independent mechanisms underlying acquisition and restoration of anchorage-independent growth in HR+ tumors. Combined analysis of tumor and microenvironmental biomarkers in metastatic biopsies of HT-resistant patients can help refine treatment approaches.Significance:This study uncovers a previously underappreciated dependency of tumor cells on HR signaling for anchorage-independent growth and highlights how the metastatic microenvironment restores this malignant property of cancer cells during hormone therapy.

Intercellular communication between axons and Schwann cells is critical for attaining the complex morphological steps necessary for axon maturation. In the early onset motor neuron disease spinal muscular atrophy (SMA), many motor axons are not ensheathed by Schwann cells nor grow sufficiently in radial diameter to become myelinated. These developmentally arrested motor axons are dysfunctional and vulnerable to rapid degeneration, limiting efficacy of current SMA therapeutics. We hypothesized that accelerating SMA motor axon maturation would improve their function and reduce disease features. A principle regulator of peripheral axon development is neuregulin 1 type III (NRG1-III). Expressed on axon surfaces, it interacts with Schwann cell receptors to mediate axon ensheathment and myelination. We examined NRG1 mRNA and protein expression levels in human and mouse SMA tissues and observed reduced expression in SMA spinal cord and in ventral, but not dorsal root axons. To determine the impact of neuronal NRG1-III overexpression on SMA motor axon development, we bred NRG1-III overexpressing mice to SMA∆7 mice. Neonatally, elevated NRG1-III expression increased SMA ventral root size as well as axon segregation, diameter, and myelination resulting in improved motor axon conduction velocities. NRG1-III was not able to prevent distal axonal degeneration nor improve axon electrophysiology, motor behavior, or survival of older mice. Together these findings demonstrate that early SMA motor axon developmental impairments can be ameliorated by a molecular strategy independent of SMN replacement providing hope for future SMA combinatorial therapeutic approaches.

Multivalency plays a key role in achieving strong, yet reversible interactions in nature, and provides critical chemical organization in biological recognition processes. Chemists have taken an interest in designing multivalent synthetic assemblies to both better understand the underlying principles governing these interactions, and to build chemical tools that either enhance or prevent such recognition events from occurring in biology. Rationally tailoring synthetic strategies to achieve the high level of chemical control and tunability required to mimic these interactions, however, is challenging. Here, we introduce a systematic and modular synthetic approach to the design of well-defined molecular multivalent protein-binding constructs that allows for control over size, morphology, and valency. A series of supramolecular mono-, bi-, and tetrametallic Fe(ii) complexes featuring a precise display of peripheral saccharides was prepared through coordination-driven self-assembly from simple building blocks. The molecular assemblies are fully characterized, and we present the structural determination of one complex in the series. The mannose and maltose-appended assemblies display strong multivalent binding to model lectin, Concanavalin A (K d values in μM), where the strength of the binding is a direct consequence of the number of saccharide units decorating the molecular periphery. This versatile synthetic strategy provides chemical control while offering an easily accessible approach to examine important design principles governing structure-function relationships germane to biological recognition and binding properties.

Purpose Mortality prediction in elderly femoral neck fracture patients is valuable in treatment decision-making. A previously developed and internally validated clinical prediction model shows promise in identifying patients at risk of 90-day and 2-year mortality. Validation in an independent cohort is required to assess the generalizability; especially in geographically distinct regions. Therefore we questioned, is the SORG Orthopaedic Research Group (SORG) femoral neck fracture mortality algorithm externally valid in an Israeli cohort to predict 90-day and 2-year mortality? Methods We previously developed a prediction model in 2022 for estimating the risk of mortality in femoral neck fracture patients using a multicenter institutional cohort of 2,478 patients from the USA. The model included the following input variables that are available on clinical admission: age, male gender, creatinine level, absolute neutrophil, hemoglobin level, international normalized ratio (INR), congestive heart failure (CHF), displaced fracture, hemiplegia, chronic obstructive pulmonary disease (COPD), history of cerebrovascular accident (CVA) and beta-blocker use. To assess the generalizability, we used an intercontinental institutional cohort from the Sheba Medical Center in Israel (level I trauma center), queried between June 2008 and February 2022. Generalizability of the model was assessed using discrimination, calibration, Brier score, and decision curve analysis. Results The validation cohort included 2,033 patients, aged 65 years or above, that underwent femoral neck fracture surgery. Most patients were female 64.8% (n = 1317), the median age was 81 years (interquartile range = 75–86), and 80.4% (n = 1635) patients sustained a displaced fracture (Garden III/IV). The 90-day mortality was 9.4% (n = 190) and 2-year mortality was 30.0% (n = 610). Despite numerous baseline differences, the model performed acceptably to the validation cohort on discrimination (c-statistic 0.67 for 90-day, 0.67 for 2-year), calibration, Brier score, and decision curve analysis. Conclusions The previously developed SORG femoral neck fracture mortality algorithm demonstrated good performance in an independent intercontinental population. Current iteration should not be relied on for patient care, though suggesting potential utility in assessing patients at low risk for 90-day or 2-year mortality. Further studies should evaluate this tool in a prospective setting and evaluate its feasibility and efficacy in clinical practice. The algorithm can be freely accessed: https://sorg-apps.shinyapps.io/hipfracturemortality/. Level of evidence Level III, Prognostic study.

BACKGROUND The outcome differences following surgery for an impending versus a completed pathological fracture have not been clearly defined. The purpose of the present study was to assess differences in outcomes following the surgical treatment of impending versus completed pathological fractures in patients with long-bone metastases in terms of (1) 90-day and 1-year survival and (2) intraoperative blood loss, perioperative blood transfusion, anesthesia time, duration of hospitalization, 30-day postoperative systemic complications, and reoperations. METHODS We retrospectively performed a matched cohort study utilizing a database of 1,064 patients who had undergone operative treatment for 462 impending and 602 completed metastatic long-bone fractures. After matching on 22 variables, including primary tumor, visceral metastases, and surgical treatment, 270 impending pathological fractures were matched to 270 completed pathological fractures. The primary outcome was assessed with the Cox proportional hazard model. The secondary outcomes were assessed with the McNemar test and the Wilcoxon signed-rank test. RESULTS The 90-day survival rate did not differ between the groups (HR, 1.13 [95% CI, 0.81 to 1.56]; p = 0.48), but the 1-year survival rate was worse for completed pathological fractures (46% versus 38%) (HR, 1.28 [95% CI, 1.02 to 1.61]; p = 0.03). With regard to secondary outcomes, completed pathological fractures were associated with higher intraoperative estimated blood loss (p = 0.03), a higher rate of perioperative blood transfusions (p = 0.01), longer anesthesia time (p = 0.04), and more reoperations (OR, 2.50 [95% CI, 1.92 to 7.86]; p = 0.03); no differences were found in terms of the rate of 30-day postoperative complications or the duration of hospitalization. CONCLUSIONS Patients undergoing surgery for impending pathological fractures had lower 1-year mortality rates and better secondary outcomes as compared with patients undergoing surgery for completed pathological fractures when accounting for 22 covariates through propensity matching. Patients with an impending pathological fracture appear to benefit from prophylactic stabilization as stabilizing a completed pathological fracture seems to be associated with increased mortality, blood loss, rate of blood transfusions, duration of surgery, and reoperation risk. LEVEL OF EVIDENCE Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Background Local recurrence of microinvasive sarcoma or benign aggressive pathologies can be limb- and life-threatening. Although frozen pathology is reliable, tumor microinvasion can be subtle or missed, having an impact on surgical margins and postoperative radiation planning. The authors' service has begun to temporize the tumor bed after primary tumor excision with a wound vacuum-assisted closure (VAC) pending formal margin analysis, with coverage performed in the setting of final negative margins. Methods This retrospective analysis included all patients managed at a tertiary referral cancer center with VAC temporization after soft tissue sarcoma or benign aggressive tumor excision from 1 January 2000 to 1 January 2019 and at least 2 years of oncologic follow-up evaluation. The primary outcome was local recurrence. The secondary outcomes were distant recurrence, unplanned return to the operating room for wound/infectious indications, thromboembolic events, and tumor-related deaths. Results For 62 patients, VAC temporization was performed. The mean age of the patients was 62.2 ± 22.3 years (median 66.5 years; 95% confidence interval [CI] 61.7-72.5 years), and the mean age-adjusted Charlson Comorbidity Index was 5.3 ± 1.9. The most common tumor histology was myxofibrosarcoma (51.6%, 32/62). The mean volume was 124.8 ± 324.1 cm3, and 35.5% (22/62) of the cases were subfascial. Local recurrences occurred for 8.1% (5/62) of the patients. Three of these five patients had planned positive margins, and 17.7% (11/62) of the patients had an unplanned return to the operating room. No demographic or tumor factors were associated with unplanned surgery. Conclusions The findings showed that VAC-temporized management of microinvasive sarcoma and benign aggressive pathologies yields favorable local recurrence and unplanned operating room rates suggestive of oncologic and technical safety. These findings will need validation in a future randomized controlled trial.

Purpose This study aimed to investigate spine surgeons’ ability to estimate survival in patients with spinal metastases and whether survival estimates influence treatment recommendations. Methods 60 Spine surgeons were asked a survival estimate and treatment recommendation in 12 cases. Intraclass correlation coefficients and descriptive statistics were used to evaluate variability, accuracy and association of survival estimates with treatment recommendation. Results There was substantial variability in survival estimates amongst the spine surgeons. Survival was generally overestimated, and longer estimated survival seemed to lead to more invasive procedures. Conclusions Prognostic models to estimate survival may aid surgeons treating patients with spinal metastases.

➤ As the Patient-Reported Outcomes Measurement Information System (PROMIS) is increasingly utilized in orthopaedic research and clinical practice, there is not a consensus regarding the minimum clinically important difference (MCID) calculation. ➤ The varied MCID calculation methods can lead to a range of possible values, which limits the translatability of research efforts. ➤ The completion rate and follow-up period also influence MCID values and should be reported alongside study results.

Background and purpose — Advancements in software and hardware have enabled the rise of clinical prediction models based on machine learning (ML) in orthopedic surgery. Given their growing popularity and their likely implementation in clinical practice we evaluated which outcomes these new models have focused on and what methodologies are being employed. Material and methods — We performed a systematic search in PubMed, Embase, and Cochrane Library for studies published up to June 18, 2020. Studies reporting on non-ML prediction models or non-orthopedic outcomes were excluded. After screening 7,138 studies, 59 studies reporting on 77 prediction models were included. We extracted data regarding outcome, study design, and reported performance metrics. Results — Of the 77 identified ML prediction models the most commonly reported outcome domain was medical management (17/77). Spinal surgery was the most commonly involved orthopedic subspecialty (28/77). The most frequently employed algorithm was neural networks (42/77). Median size of datasets was 5,507 (IQR 635–26,364). The median area under the curve (AUC) was 0.80 (IQR 0.73–0.86). Calibration was reported for 26 of the models and 14 provided decision-curve analysis. Interpretation — ML prediction models have been developed for a wide variety of topics in orthopedics. Topics regarding medical management were the most commonly studied. Heterogeneity between studies is based on study size, algorithm, and time-point of outcome. Calibration and decision-curve analysis were generally poorly reported.

BACKGROUND Intraoperative vascular injury (VI) may be an unavoidable complication of anterior lumbar spine surgery; however, vascular injury has implications for quality and safety reporting as this intraoperative complication may result in serious bleeding, thrombosis, and postoperative stricture. PURPOSE The purpose of this study was to (1) develop machine learning algorithms for preoperative prediction of VI and (2) develop natural language processing (NLP) algorithms for automated surveillance of intraoperative VI from free-text operative notes. PATIENT SAMPLE Adult patients, 18 years or age or older, undergoing anterior lumbar spine surgery at two academic and three community medical centers were included in this analysis. OUTCOME MEASURES The primary outcome was unintended VI during anterior lumbar spine surgery. METHODS Manual review of free-text operative notes was used to identify patients who had unintended VI. The available population was split into training and testing cohorts. Five machine learning algorithms were developed for preoperative prediction of VI. An NLP algorithm was trained for automated detection of intraoperative VI from free-text operative notes. Performance of the NLP algorithm was compared to current procedural terminology and international classification of diseases codes. RESULTS In all, 1035 patients underwent anterior lumbar spine surgery and the rate of intraoperative VI was 7.2% (n=75). Variables used for preoperative prediction of VI were age, male sex, body mass index, diabetes, L4-L5 exposure, and surgery for infection (discitis, osteomyelitis). The best performing machine learning algorithm achieved c-statistic of 0.73 for preoperative prediction of VI ( https://sorg-apps.shinyapps.io/lumbar_vascular_injury/ ). For automated detection of intraoperative VI from free-text notes, the NLP algorithm achieved c-statistic of 0.92. The NLP algorithm identified 18 of the 21 patients (sensitivity 0.86) who had a VI whereas current procedural terminologyand international classification of diseases codes identified 6 of the 21 (sensitivity 0.29) patients. At this threshold, the NLP algorithm had a specificity of 0.93, negative predictive value of 0.99, positive predictive value of 0.51, and F1-score of 0.64. CONCLUSION Relying on administrative procedural and diagnosis codes may underestimate the rate of unintended intraoperative VI in anterior lumbar spine surgery. External and prospective validation of the algorithms presented here may improve quality and safety reporting.