How Did Black and Hispanic Orthopaedic Applicants and Residents Compare to General Surgery Between 2015 and 2022?

Despite the heavy demand for and knowledge of the benefits of diversity, there is a persistent lack of racial, ethnic, and gender diversity in orthopaedic surgery. Since the implementation of diversity initiatives, data have shown that general surgery has been one of the top competitive surgical fields and has demonstrated growth in racial, ethnic, and gender diversity, making general surgery a good point of reference and comparison when analyzing racial and ethnic growth in orthopaedic surgery. (1) What were the growth rates for Black and Hispanic orthopaedic residency applicants and residents between 2015 and 2022? (2) How did the growth rates of Black and Hispanic individuals in orthopaedic surgery compare with those of general surgery? (3) How did applicant recruitment and resident acceptance differ between Black and Hispanic people in orthopaedic surgery? Applicant data were obtained from historical specialty-specific data from the Association of American Medical Colleges Electronic Residency Application Service Statistics database between 2018 and 2022, and resident data were obtained from the Accreditation Council of Graduate Medical Education Data Resource Book between 2015 and 2021. Between 2018 and 2022, the number of residency applicants totaled 216,677, with 17,912 Black residency applicants and 20,413 Hispanic residency applicants. Between 2015 and 2021, the number of active residents totaled 977,877, with 48,600 Black residents and 62,605 Hispanic residents. Because the applicant and resident data do not overlap throughout all years of observation, a sensitivity analysis of overlapping years (between 2018 and 2021) was conducted to ensure observed trends were consistent and valid throughout the study. All datasets obtained were used to establish the different racial and ethnic proportions of Black and Hispanic residency applicants and residents in four nonsurgical primary care specialties and four surgical subspecialties. A reference slope was created using data from the Association of American Medical Colleges and Accreditation Council of Graduate Medical Education to represent the growth rate for total residency applicants and residents, independently, across all residency specialties reported in each database. This slope was used for comparison among the resident and applicant growth rates for all eight selected specialties. Datapoints were placed into a scatterplot with regression lines, using slope equations to depict rate of growth and R 2 values to depict linear fit. Applicant growth corresponded to applicant recruitment and resident growth corresponded to resident acceptance. Chi-square tests were used to compare residents and residency applicants for the Black and Hispanic populations, separately. Two-way analysis of variance with a time-by-specialty interaction term (F-test) was conducted to determine differences between growth slopes. There was no difference in the growth rate of Black orthopaedic surgery applicants between 2018 and 2022, and there was no difference in the growth rate of Hispanic orthopaedic surgery applicants (R 2 = 0.43; p = 0.23 and R 2 = 0.63; p = 0.11, respectively). However, there was a very slight increase in the growth rate of Black orthopaedic surgery residents between 2015 and 2021, and a very slight increase in the growth rate of Hispanic orthopaedic surgery residents (R 2 = 0.73; p = 0.02 and R 2 = 0.79; p = 0.01, respectively). There were no differences in orthopaedic and general surgery rates of growth for Black applicants between 2018 and 2022 (0.004 applicants/year versus -0.001 applicants/year; p = 0.22), and no differences were found in orthopaedic and general surgery rates of growth for Black residents between 2015 and 2021 (0.003 residents/year versus 0.002 residents/year; p = 0.59). Likewise, Hispanic orthopaedic applicant growth rates did not differ between 2018 and 2022 from the rates of general surgery (0.004 applicants/year versus 0.005 applicants/year; p = 0.68), and there were no differences in orthopaedic and general surgery rates of growth for Hispanic residents (0.007 residents/year versus 0.01 residents/year; p = 0.35). Furthermore, growth rate comparisons between Black orthopaedic applicants and residents between 2018 and 2021 showed applicant growth was larger than resident growth, illustrating that the recruitment of Black applicants increased slightly more rapidly than resident acceptance. Growth rate comparisons between Hispanic applicants and residents showed a larger rate of resident growth, illustrating Hispanic resident acceptance increased slightly faster than applicant recruitment during that time. We found low acceptance of Black residents compared with the higher recruitment of Black applicants, as well as overall low proportions of Black and Hispanic applicants and residents. Future studies might explore the factors contributing to the higher acceptances of Hispanic orthopaedic residents than Black orthopaedic residents. We recommend that more emphasis should be placed on increasing Black and Hispanic representation at the department level to ensure cultural considerations remain at the forefront of applicant recruitment. Internal or external reviews of residency selection processes should be considered, and more immersive, longitudinal orthopaedic surgery clerkships and research mentorship experiences should be targeted toward Black and Hispanic students. Holistic reviews of applications and selection processes should be implemented to produce an increased racially and ethnically diverse applicant pool and a diverse residency work force, and implicit bias training should be implemented to address potential biases and diversity barriers that are present in residency programs and leadership.

Williams AJ ，Malewicz JI ，Pum JM ，Zurakowski D ，Day CS ... -  《-》

What are the Trends in Racial Diversity Among Orthopaedic Applicants, Residents, and Faculty?

Orthopaedic surgery has recruited fewer applicants from underrepresented in medicine (UIM) racial groups than many other specialties, and recent studies have shown that although applicants from UIM racial groups are competitive for orthopaedic surgery, they enter the specialty at lower rates. Although previous studies have measured trends in orthopaedic surgery applicant, resident, or attending diversity in isolation, these populations are interdependent and therefore should be analyzed together. It is unclear how racial diversity among orthopaedic applicants, residents, and faculty has changed over time and how it compares with other surgical and medical specialties. (1) How has the proportion of orthopaedic applicants, residents, and faculty from UIM and White racial groups changed between 2016 and 2020? (2) How does representation of orthopaedic applicants from UIM and White racial groups compare with that of other surgical and medical specialties? (3) How does representation of orthopaedic residents from UIM and White racial groups compare with that of other surgical and medical specialties? (4) How does representation of orthopaedic faculty from UIM and White racial groups compare with that of other surgical and medical specialties? We drew racial representation data for applicants, residents, and faculty between 2016 and 2020. Applicant data on racial groups was obtained for 10 surgical and 13 medical specialties from the Association of American Medical Colleges Electronic Residency Application Services report, which annually publishes demographic data on all medical students applying to residency through Electronic Residency Application Services. Resident data on racial groups were obtained for the same 10 surgical and 13 medical specialties from the Journal of the American Medical Association Graduate Medical Education report, which annually publishes demographic data on residents in residency training programs accredited by the Accreditation Council for Graduate Medical Education. Faculty data on racial groups were obtained for four surgical and 12 medical specialties from the Association of American Medical Colleges Faculty Roster United States Medical School Faculty report, which annually publishes demographic data of active faculty at United States allopathic medical schools. UIM racial groups include American Indian or Alaska Native, Black or African American, Hispanic or Latino, and Native American or Other Pacific Islander. Chi-square tests were performed to compare representation of UIM and White groups among orthopaedic applicants, residents, and faculty between 2016 and 2020. Further, chi-square tests were performed to compare aggregate representation of applicants, residents, and faculty from UIM and White racial groups in orthopaedic surgery to aggregate representation among other surgical and medical specialties with available data. The proportion of orthopaedic applicants from UIM racial groups increased between 2016 to 2020 from 13% (174 of 1309) to 18% (313 of 1699, absolute difference 0.051 [95% CI 0.025 to 0.078]; p < 0.001). The proportion of orthopaedic residents (9.6% [347 of 3617] to 10% [427 of 4242]; p = 0.48) and faculty (4.7% [186 of 3934] to 4.7% [198 of 4234]; p = 0.91) from UIM racial groups did not change from 2016 to 2020. There were more orthopaedic applicants from UIM racial groups (15% [1151 of 7446]) than orthopaedic residents from UIM racial groups (9.8% [1918 of 19,476]; p < 0.001). There were also more orthopaedic residents from UIM groups (9.8% [1918 of 19,476]) than orthopaedic faculty from UIM groups (4.7% [992 of 20,916], absolute difference 0.051 [95% CI 0.046 to 0.056]; p < 0.001). The proportion of orthopaedic applicants from UIM groups (15% [1151 of 7446]) was greater than that of applicants to otolaryngology (14% [446 of 3284], absolute difference 0.019 [95% CI 0.004 to 0.033]; p = 0.01), urology (13% [319 of 2435], absolute difference 0.024 [95% CI 0.007 to 0.039]; p = 0.005), neurology (12% [1519 of 12,862], absolute difference 0.036 [95% CI 0.027 to 0.047]; p < 0.001), pathology (13% [1355 of 10,792], absolute difference 0.029 [95% CI 0.019 to 0.039]; p < 0.001), and diagnostic radiology (14% [1635 of 12,055], absolute difference 0.019 [95% CI 0.009 to 0.029]; p < 0.001), and it was not different from that of applicants to neurosurgery (16% [395 of 2495]; p = 0.66), plastic surgery (15% [346 of 2259]; p = 0.87), interventional radiology (15% [419 of 2868]; p = 0.28), vascular surgery (17% [324 of 1887]; p = 0.07), thoracic surgery (15% [199 of 1294]; p = 0.94), dermatology (15% [901 of 5927]; p = 0.68), internal medicine (15% [18,182 of 124,214]; p = 0.05), pediatrics (16% [5406 of 33,187]; p = 0.08), and radiation oncology (14% [383 of 2744]; p = 0.06). The proportion of orthopaedic residents from UIM groups (9.8% [1918 of 19,476]) was greater than UIM representation among residents in otolaryngology (8.7% [693 of 7968], absolute difference 0.012 [95% CI 0.004 to 0.019]; p = 0.003), interventional radiology (7.4% [51 of 693], absolute difference 0.025 [95% CI 0.002 to 0.043]; p = 0.03), and radiation oncology (7.9% [289 of 3659], absolute difference 0.020 [95% CI 0.009 to 0.029]; p < 0.001), and it was not different from UIM representation among residents in plastic surgery (9.3% [386 of 4129]; p = 0.33), urology (9.7% [670 of 6877]; p = 0.80), dermatology (9.9% [679 of 6879]; p = 0.96), and diagnostic radiology (10% [2215 of 22,076]; p = 0.53). The proportion of orthopaedic faculty from UIM groups (4.7% [992 of 20,916]) was not different from UIM representation among faculty in otolaryngology (4.8% [553 of 11,413]; p = 0.68), neurology (5.0% [1533 of 30,871]; p = 0.25), pathology (4.9% [1129 of 23,206]; p = 0.55), and diagnostic radiology (4.9% [2418 of 49,775]; p = 0.51). Compared with other surgical and medical specialties with available data, orthopaedic surgery had the highest proportion of White applicants (62% [4613 of 7446]), residents (75% [14,571 of 19,476]), and faculty (75% [15,785 of 20,916]). Orthopaedic applicant representation from UIM groups has increased over time and is similar to that of several surgical and medical specialties, suggesting relative success with efforts to recruit more students from UIM groups. However, the proportion of orthopaedic residents and UIM groups has not increased accordingly, and this is not because of a lack of applicants from UIM groups. In addition, UIM representation among orthopaedic faculty has not changed and may be partially explained by the lead time effect, but increased attrition among orthopaedic residents from UIM groups and racial bias likely also play a role. Further interventions and research into the potential difficulties faced by orthopaedic applicants, residents, and faculty from UIM groups are necessary to continue making progress. A diverse physician workforce is better suited to address healthcare disparities and provide culturally competent patient care. Representation of orthopaedic applicants from UIM groups has improved over time, but further research and interventions are necessary to diversify orthopaedic surgery to ultimately provide better care for all orthopaedic patients.

Kalyanasundaram G ，Mener A ，DiCaprio MR 《-》

Defining the optimum strategy for identifying adults and children with coeliac disease: systematic review and economic modelling.

Elwenspoek MM ，Thom H ，Sheppard AL ，Keeney E ，O'Donnell R ，Jackson J ，Roadevin C ，Dawson S ，Lane D ，Stubbs J ，Everitt H ，Watson JC ，Hay AD ，Gillett P ，Robins G ，Jones HE ，Mallett S ，Whiting PF ... -  《-》

Falls prevention interventions for community-dwelling older adults: systematic review and meta-analysis of benefits, harms, and patient values and preferences.

About 20-30% of older adults (≥ 65 years old) experience one or more falls each year, and falls are associated with substantial burden to the health care system, individuals, and families from resulting injuries, fractures, and reduced functioning and quality of life. Many interventions for preventing falls have been studied, and their effectiveness, factors relevant to their implementation, and patient preferences may determine which interventions to use in primary care. The aim of this set of reviews was to inform recommendations by the Canadian Task Force on Preventive Health Care (task force) on fall prevention interventions. We undertook three systematic reviews to address questions about the following: (i) the benefits and harms of interventions, (ii) how patients weigh the potential outcomes (outcome valuation), and (iii) patient preferences for different types of interventions, and their attributes, shown to offer benefit (intervention preferences). We searched four databases for benefits and harms (MEDLINE, Embase, AgeLine, CENTRAL, to August 25, 2023) and three for outcome valuation and intervention preferences (MEDLINE, PsycINFO, CINAHL, to June 9, 2023). For benefits and harms, we relied heavily on a previous review for studies published until 2016. We also searched trial registries, references of included studies, and recent reviews. Two reviewers independently screened studies. The population of interest was community-dwelling adults ≥ 65 years old. We did not limit eligibility by participant fall history. The task force rated several outcomes, decided on their eligibility, and provided input on the effect thresholds to apply for each outcome (fallers, falls, injurious fallers, fractures, hip fractures, functional status, health-related quality of life, long-term care admissions, adverse effects, serious adverse effects). For benefits and harms, we included a broad range of non-pharmacological interventions relevant to primary care. Although usual care was the main comparator of interest, we included studies comparing interventions head-to-head and conducted a network meta-analysis (NMAs) for each outcome, enabling analysis of interventions lacking direct comparisons to usual care. For benefits and harms, we included randomized controlled trials with a minimum 3-month follow-up and reporting on one of our fall outcomes (fallers, falls, injurious fallers); for the other questions, we preferred quantitative data but considered qualitative findings to fill gaps in evidence. No date limits were applied for benefits and harms, whereas for outcome valuation and intervention preferences we included studies published in 2000 or later. All data were extracted by one trained reviewer and verified for accuracy and completeness. For benefits and harms, we relied on the previous review team's risk-of-bias assessments for benefit outcomes, but otherwise, two reviewers independently assessed the risk of bias (within and across study). For the other questions, one reviewer verified another's assessments. Consensus was used, with adjudication by a lead author when necessary. A coding framework, modified from the ProFANE taxonomy, classified interventions and their attributes (e.g., supervision, delivery format, duration/intensity). For benefit outcomes, we employed random-effects NMA using a frequentist approach and a consistency model. Transitivity and coherence were assessed using meta-regressions and global and local coherence tests, as well as through graphical display and descriptive data on the composition of the nodes with respect to major pre-planned effect modifiers. We assessed heterogeneity using prediction intervals. For intervention-related adverse effects, we pooled proportions except for vitamin D for which we considered data in the control groups and undertook random-effects pairwise meta-analysis using a relative risk (any adverse effects) or risk difference (serious adverse effects). For outcome valuation, we pooled disutilities (representing the impact of a negative event, e.g. fall, on one's usual quality of life, with 0 = no impact and 1 = death and ~ 0.05 indicating important disutility) from the EQ-5D utility measurement using the inverse variance method and a random-effects model and explored heterogeneity. When studies only reported other data, we compared the findings with our main analysis. For intervention preferences, we used a coding schema identifying whether there were strong, clear, no, or variable preferences within, and then across, studies. We assessed the certainty of evidence for each outcome using CINeMA for benefit outcomes and GRADE for all other outcomes. A total of 290 studies were included across the reviews, with two studies included in multiple questions. For benefits and harms, we included 219 trials reporting on 167,864 participants and created 59 interventions (nodes). Transitivity and coherence were assessed as adequate. Across eight NMAs, the number of contributing trials ranged between 19 and 173, and the number of interventions ranged from 19 to 57. Approximately, half of the interventions in each network had at least low certainty for benefit. The fallers outcome had the highest number of interventions with moderate certainty for benefit (18/57). For the non-fall outcomes (fractures, hip fracture, long-term care [LTC] admission, functional status, health-related quality of life), many interventions had very low certainty evidence, often from lack of data. We prioritized findings from 21 interventions where there was moderate certainty for at least some benefit. Fourteen of these had a focus on exercise, the majority being supervised (for > 2 sessions) and of long duration (> 3 months), and with balance/resistance and group Tai Chi interventions generally having the most outcomes with at least low certainty for benefit. None of the interventions having moderate certainty evidence focused on walking. Whole-body vibration or home-hazard assessment (HHA) plus exercise provided to everyone showed moderate certainty for some benefit. No multifactorial intervention alone showed moderate certainty for any benefit. Six interventions only had very-low certainty evidence for the benefit outcomes. Two interventions had moderate certainty of harmful effects for at least one benefit outcome, though the populations across studies were at high risk for falls. Vitamin D and most single-component exercise interventions are probably associated with minimal adverse effects. Some uncertainty exists about possible adverse effects from other interventions. For outcome valuation, we included 44 studies of which 34 reported EQ-5D disutilities. Admission to long-term care had the highest disutility (1.0), but the evidence was rated as low certainty. Both fall-related hip (moderate certainty) and non-hip (low certainty) fracture may result in substantial disutility (0.53 and 0.57) in the first 3 months after injury. Disutility for both hip and non-hip fractures is probably lower 12 months after injury (0.16 and 0.19, with high and moderate certainty, respectively) compared to within the first 3 months. No study measured the disutility of an injurious fall. Fractures are probably more important than either falls (0.09 over 12 months) or functional status (0.12). Functional status may be somewhat more important than falls. For intervention preferences, 29 studies (9 qualitative) reported on 17 comparisons among single-component interventions showing benefit. Exercise interventions focusing on balance and/or resistance training appear to be clearly preferred over Tai Chi and other forms of exercise (e.g., yoga, aerobic). For exercise programs in general, there is probably variability among people in whether they prefer group or individual delivery, though there was high certainty that individual was preferred over group delivery of balance/resistance programs. Balance/resistance exercise may be preferred over education, though the evidence was low certainty. There was low certainty for a slight preference for education over cognitive-behavioral therapy, and group education may be preferred over individual education. To prevent falls among community-dwelling older adults, evidence is most certain for benefit, at least over 1-2 years, from supervised, long-duration balance/resistance and group Tai Chi interventions, whole-body vibration, high-intensity/dose education or cognitive-behavioral therapy, and interventions of comprehensive multifactorial assessment with targeted treatment plus HHA, HHA plus exercise, or education provided to everyone. Adding other interventions to exercise does not appear to substantially increase benefits. Overall, effects appear most applicable to those with elevated fall risk. Choice among effective interventions that are available may best depend on individual patient preferences, though when implementing new balance/resistance programs delivering individual over group sessions when feasible may be most acceptable. Data on more patient-important outcomes including fall-related fractures and adverse effects would be beneficial, as would studies focusing on equity-deserving populations and on programs delivered virtually. Not registered.

Pillay J ，Gaudet LA ，Saba S ，Vandermeer B ，Ashiq AR ，Wingert A ，Hartling L ... -  《Systematic Reviews》

Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.

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. (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? 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. 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. 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 III, diagnostic study.

Lee CC ，Chen CW ，Yen HK ，Lin YP ，Lai CY ，Wang JL ，Groot OQ ，Janssen SJ ，Schwab JH ，Hsu FM ，Lin WH ... -  《-》