bims-rebome 2025-10-26 papers

bims-rebome

Biomed News

on Rehabilitation of bone metastases

Issue of 2025–10–26
six papers selected by
Alberto Selvanetti, Azienda Ospedaliera San Giovanni Addolorata

A systematic review of the spinal instability neoplastic score and its relationship with peri-interventional patient-centered measures: The clinical impact of spinal instability.
External evaluation of the SORG machine learning algorithm predicting 90-day and 1-year mortality in a Midwest cohort of patients with spinal metastasis.
Orthopedic interventions and outcomes in patients with metastatic renal cell carcinoma: a systematic review.
Outcomes of Retreatment for Local Recurrence After Surgery for Metastatic Spine Cancer: A Multicenter Study.
Development and validation of prognostic models for bone metastasis in Non-Small cell lung cancer based on Machine learning algorithms.
Immune checkpoint inhibitors combined with chemotherapy as first-line treatment may improve clinical outcomes in advanced non-small cell lung cancer with bone metastases.

Medicine (Baltimore). 2025 Oct 24. 104(43): e44992

A systematic review of the spinal instability neoplastic score and its relationship with peri-interventional patient-centered measures: The clinical impact of spinal instability.

Hassan Darabi, Harshit Arora, Henry Ruiz-Garcia, Aysha Alsahlawi, Jared T Wilcox, Francis Farhadi.

   BACKGROUND: The spinal instability neoplastic score (SINS) provides a standardized assessment of spinal stability in patients with metastatic spine disease. Although intended to assist clinical decision-making, the relationships between SINS and patient-centered measures, such as pain intensity, functional status, and health-related quality of life (HRQoL), remain undefined.
METHODS: This systematic review followed PRISMA guidelines. A comprehensive literature search was performed across PubMed, Scopus, Embase, and Web of Science databases using keywords related to SINS and spinal metastases. Studies assessing the relationships between SINS and pain intensity scores, functional status, and HRQoL were included. Data on study characteristics, type of interventions, and patient-centered measures were extracted. Risk of bias was assessed using the Newcastle-Ottawa Scale. A meta-analysis was not feasible due to significant treatment, outcome, and population heterogeneity.
RESULTS: Thirteen studies (n = 1823; mean age 63.0 ± 12.5 years) were included. Five of six studies reported a significant association between higher baseline SINS scores and pain intensity, most commonly using the Visual Analog Scale and Numeric Rating, while 1 of 2 studies identified a predictive value of SINS for posttreatment pain. Nine studies evaluated peri-interventional functional status using 6 different tools; significant correlations with baseline SINS were identified for MD Anderson Symptom Inventory and Spine Oncology Study Group Outcomes Questionnaire 2.0, while no relationships were identified for the Barthel Index, Eastern Cooperative Oncology Group score, or Frankel scale. Further, stable postradiotherapy SINS was associated a higher baseline Karnofsky Performance Status (KPS). Three studies assessed HRQoL using either the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30, the 36-Item Short Form Survey, or the EuroQol Five-Dimension Scale; 2 of these studies reported that higher SINS values were associated with lower baseline physical functioning. Of 13 studies, 12 were of moderate methodological quality.
CONCLUSIONS: SINS demonstrated correlations with peri-interventional pain intensity, functional status, and HRQoL. Pretreatment correlations were generally more consistent. However, in radiotherapy-treated cohorts, stable posttreatment SINS was associated with higher baseline KPS, suggesting a potential predictive relationship between these measures.

Keywords:  functional status; pain outcomes; patient-reported outcomes; quality of life; spinal instability; spinal metastasis

DOI:  https://doi.org/10.1097/MD.0000000000044992
J Clin Neurosci. 2025 Oct 19. pii: S0967-5868(25)00647-2. [Epub ahead of print]142 111674

External evaluation of the SORG machine learning algorithm predicting 90-day and 1-year mortality in a Midwest cohort of patients with spinal metastasis.

Kyle W Geiger, James R L Hall, Michael Garneau, Trevor R Gulbrandsen, Alex R Coffman, Reagan A Grieser-Yoder, Harmen R Kuijten, Olivier Q Groot, Cassim M Igram, Andrew J Pugely, Catherine R Olinger, Joseph H Schwab.

   BACKGROUND CONTEXT: The Skeletal Oncology Research Group (SORG) machine learning algorithm was developed in 2019 to predict 90-day and 1-year mortality for patients with spinal metastatic disease. With an increasing prevalence of spinal metastasis and the associated rise in surgical intervention, our group sought to improve accuracy in estimating intermediate and long-term post-operative survival to better inform the shared decision-making process of the patient and surgeon regarding the next steps in care. The SORG algorithm was developed based on a cohort of patients residing in the Northeastern United States but has yet to be evaluated in a rural Midwest cohort.
PURPOSE: The purpose of this study was to externally evaluate the accuracy of the SORG algorithm among a cohort of patients in the Midwest region of the United States.
STUDY DESIGN/SETTING: This external validation study is a retrospective study with data from a Midwest cohort at a single institution.
PATIENT SAMPLE: Patients aged 18 and older who underwent surgical treatment for spinal metastasis between 2010 and 2022 at [redacted] were included in this retrospective study.
OUTCOME MEASURES: Outcome measures included discrimination (c-statistic and receiver operating curve), calibration (calibration slope, intercept, calibration plot, and observed proportions by predicted risk groups), overall performance (Brier score), and decision curve analysis.
METHODS: Baseline characteristics of the validation cohort were obtained and compared to the developmental cohort. Discrimination, calibration, overall performance, and decision curve analysis were used to assess the SORG machine learning algorithm in the validation cohort.
RESULTS: Overall, there were 247 patients included in this study with 90-day and 1-year mortality rates of 63 (25%) and 134 (54%), respectively. The validation cohort and the developmental cohort differed significantly regarding primary tumor histology, the presence of visceral metastasis, and pre-operative hemoglobin levels. The SORG algorithm for 90-day and 1-year mortality showed strong discrimination ability (AUC 0.85 [95% confidence interval [CI] 0.74 to 0.94] and 0.82 [95% CI 0.71 to 0.91] respectively), decision curve analysis, calibration, and Brier score. The 90-day and 1-year mortality showed almost perfect calibration demonstrated by a calibration intercept of 0.06 (95% CI -0.09 to 0.21) and 0.02 (95% CI -0.12 to 0.16) respectively.
CONCLUSION: The SORG machine learning algorithm demonstrated strong generalizability in predicting 90-day and 1-year survival for patients with spinal metastatic disease in a Midwest cohort. Further validation with international patient populations and a prospective, multicenter cohort would be helpful moving forward to confirm these findings and ensure reliable integration into clinical practice.

Keywords:  External validation; Machine learning; Postoperative survival; Prediction; Prognosis; Skeletal oncology; Spinal metastasis

DOI:  https://doi.org/10.1016/j.jocn.2025.111674
Ther Adv Med Oncol. 2025 ;17 17588359251385393

Orthopedic interventions and outcomes in patients with metastatic renal cell carcinoma: a systematic review.

Abdulrahman Al Bochi, Mohamad Tarek Madani, Muhammad El-Kassem, Mohammed Fadel, Adnan Rajeh, Gabriel Boldt, Ricardo Fernandes.

   Background: Despite advanced in systemic therapy for renal cell carcinoma (RCC), bone metastasis remains an adverse prognostic factor and major cause of mortality and morbidity. Orthopedic interventions may provide symptom relief, functional recovery, and survival benefit, yet the evidence is fragmented across heterogeneous studies.
Objectives: To systematically review the outcomes of orthopedic surgical interventions in patients with symptomatic bone metastases from RCC.
Design: Systematic literature review conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.
Data sources and methods: A comprehensive search of Embase, MEDLINE, and the Cochrane Library was conducted for studies published between January 1, 2014, and January 30, 2024. Eligible studies included randomized controlled trials, prospective observational studies, and retrospective studies reporting on orthopedic interventions for RCC bone metastases. Primary outcomes included overall survival, reoperation rates, complication rates, and quality of life.
Results: Of 2208 studies screened, 15 met the inclusion criteria. All were retrospective series or case series, limiting the strength of the evidence. Six studies focused on appendicular skeleton metastases, five on axial skeleton involvement, and four on both regions. Results were primarily reported narratively, with limited statistical analyses. Orthopedic surgical interventions-particularly when combined with targeted systemic therapy-were associated with longer overall survival. Among surgical approaches, complete metastasectomy was most consistently associated with improved survival compared with intralesional curettage and stabilization-only procedures.
Conclusion: Although available data suggest that orthopedic surgery, particularly complete metastasectomy, may improve overall survival and quality of life in RCC patients with bone metastases, the evidence is limited to retrospective and narrative reports. Some studies also suggest that outcomes may be further enhanced when surgery is integrated with systemic therapy. Given the poor prognosis associated with bone involvement in RCC, prospective randomized studies are urgently needed to define optimal patient selection, standardize management strategies, and integrate surgery with systemic therapy in a multidisciplinary framework.

Keywords:  bone metastasis; orthopedic interventions; palliative therapy; radiotherapy; renal cell carcinoma; targeted therapy

DOI:  https://doi.org/10.1177/17588359251385393
Spine J. 2025 Oct 16. pii: S1529-9430(25)00861-7. [Epub ahead of print]

Outcomes of Retreatment for Local Recurrence After Surgery for Metastatic Spine Cancer: A Multicenter Study.

Sehan Park, Dong-Ho Lee, Chang Ju Hwang, Bong-Soon Chang, Hyoungmin Kim, Sam Yeol Chang, Se-Jun Park, Jin-Sung Park, Dong-Ho Kang, Young-Hoon Kim, Sang-Il Kim, Chung-Won Bang, Jae Hwan Cho.

   BACKGROUND CONTEXT: Local recurrence (LR) after surgery for metastatic spine cancer (MSC) is a challenging complication, and evidence guiding optimal retreatment strategies remains limited.
PURPOSE: To evaluate prognosis following retreatment for LR after surgery for MSC, compare treatment outcomes based on retreatment modality, and identify risk factors associated with retreatment failure.
STUDY DESIGN/SETTING: A multicenter retrospective cohort study.
PATIENT SAMPLE: Ninety-nine patients from four tertiary hospitals who developed symptomatic LR after surgery for MSC and underwent reoperation or radiation therapy (RT).
OUTCOME MEASURES: Motor grade, pain visual analog scale (VAS) score, ambulatory function, retreatment failure rate, and overall survival after LR diagnosis were assessed.
METHODS: Patients were grouped based on retreatment modality into reoperation (n=36), RT (n=38), and conservative management (n=25) groups. Conservative management included symptomatic care for LR without surgery or RT, with or without systemic treatments such as chemotherapy or hormonal therapy. Retreatment failure was defined as symptom progression despite treatment or recurrence after initial improvement. Clinical outcomes were compared among the groups, and logistic regression was performed to identify factors associated with retreatment failure.
RESULTS: Reoperation significantly improved motor grade (p=0.041) and pain VAS score (p=0.002), whereas RT and conservative treatment showed no significant improvement. Ambulatory status decreased significantly in the RT group (p=0.031) but was preserved in the reoperation group. Retreatment failure occurred in 41.9% of patients (15/36 after reoperation, 16/38 after RT; p=0.414) and was associated with increased pain (p=0.042) and reduced ambulation (p=0.012). The only significant predictor of retreatment failure was a shorter interval between initial surgery and LR (odds ratio, 0.953; p=0.045). A cutoff of 12.5 months was predictive of retreatment failure (area under the curve, 0.713; p=0.056).
CONCLUSIONS: Only reoperation resulted in significant functional improvement after retreatment for LR. RT was associated with decreased ambulatory function and did not provide significant symptom relief. Retreatment failure was common and associated with increased pain and diminished function. A significant predictor of retreatment failure was a shorter interval-less than 12.5 months-between the initial surgery and LR. These findings highlight the importance of patient selection and the limited utility of retreatment in aggressive or early-recurrent cases.

Keywords:  local recurrence; metastatic epidural spinal cord compression; metastatic spine cancer; radiation therapy; reoperation; retreatment failure

DOI:  https://doi.org/10.1016/j.spinee.2025.10.029
J Bone Oncol. 2025 Dec;55 100716

Development and validation of prognostic models for bone metastasis in Non-Small cell lung cancer based on Machine learning algorithms.

Jiabin Fang, Xiaojie Yang, Lingfeng Chen, Liuying Hong, Yingqiu He, Ji Huang, Jie Lin, Nengluan Xu, Hongru Li.

   Background: Bone is a common site of metastasis in non-small cell lung cancer (NSCLC), yet no validated prognostic model is currently available for patients presenting with bone metastases at diagnosis.
Methods: We retrospectively reviewed 1,299 NSCLC patients who underwent high-throughput sequencing between 2016 and 2023. Of these, 195 were diagnosed with bone metastases at presentation. Three machine learning algorithms were applied to identify prognostic variables. A nomogram constructed with Cox regression was used to predict overall survival (OS) and was internally validated with 1,000 bootstrap resamples.
Results: Four independent prognostic factors were identified, including age, serum calcium, monocyte-to-albumin ratio, and prognostic nutritional index. The nomogram demonstrated strong predictive performance, with areas under the curve (AUCs) of 86.53%, 78.32%, and 77.85% for 6-month, 1-year, and 2-year OS, respectively. Calibration plots showed excellent agreement between predicted and observed survival outcomes.
Conclusion: This validated nomogram provides a practical and individualized tool for predicting survival in NSCLC patients with bone metastases at diagnosis, supporting risk stratification and clinical practice.

Keywords:  Bone metastasis; Nomogram; Non-small cell lung cancer

DOI:  https://doi.org/10.1016/j.jbo.2025.100716
Transl Lung Cancer Res. 2025 Sep 30. 14(9): 3457-3467

Immune checkpoint inhibitors combined with chemotherapy as first-line treatment may improve clinical outcomes in advanced non-small cell lung cancer with bone metastases.

Yohei Asano, Katsuhiro Hayashi, Shinji Miwa, Yuta Taniguchi, Miho Okuda, Seiji Yano, Satoru Demura.

   Background: Bone metastases are common in patients with non-small cell lung cancer (NSCLC) and are associated with a poor prognosis. Although immune checkpoint inhibitors (ICIs), with or without chemotherapy, are the standard first-line treatment for advanced NSCLC, studies directly comparing their effectiveness in patients with bone metastases remain limited. With the present study, we aimed to compare the clinical effectiveness and safety of ICI monotherapy versus ICI plus chemotherapy as first-line treatments for patients with NSCLC and bone metastases.
Methods: We retrospectively analyzed 97 patients with NSCLC with bone metastases who underwent first-line treatment with ICIs and divided them into the ICI monotherapy (ICI group: n=44) and combination therapy (ICI-chemo group: n=53) groups. Primary outcomes included the bone metastasis and lung lesion response rates, overall survival (OS), progression-free survival (PFS), and the incidence of skeletal-related events (SREs) and immune-related adverse events (irAEs).
Results: The bone metastasis response rate was significantly higher in the ICI-chemo group than that in the ICI group (43.4% vs. 20.5%, P=0.01), while the lung-lesion response rate showed no significant difference (26.4% vs. 11.4%, P=0.07). The ICI-chemo group had significantly longer median OS {20.7 [95% confidence interval (CI): 14.2-51.5] vs. 16.0 (8.8-19.5) months, P=0.01} and PFS [10.4 (4.9-20.1) vs. 5.5 (3.2-8.8) months, P=0.01]. The incidence of SREs (7.5% vs. 18.2%, P=0.13) and irAEs (20.8% vs. 18.2%, P=0.81) was comparable. Multivariable analyses identified the combination therapy as an independent predictor of the bone metastasis response [odds ratio (95% CI): 0.34 (0.11-0.91), P=0.04], OS [hazard ratio (95% CI): 0.53 (0.29-0.97), P=0.03], and PFS [0.38 (0.20-0.72), P<0.01].
Conclusions: The combination of ICIs with chemotherapy as first-line treatment for patients with NSCLC and bone metastases may be associated with an improved response of bone metastases and better prognosis, while exhibiting a comparable safety profile to ICI monotherapy.

Keywords:  Non-small cell lung cancer (NSCLC); bone metastasis; chemoimmunotherapy; chemotherapy; immune checkpoint inhibitor (ICI)

DOI:  https://doi.org/10.21037/tlcr-2025-476