bims-rebome Biomed News
on Rehabilitation of bone metastases
Issue of 2025–08–17
ten papers selected by
Alberto Selvanetti, Azienda Ospedaliera San Giovanni Addolorata
  1. Social determinants are associated with clinical presentation of acute pathological fracture in metastatic long-bone disease.
  2. Risk stratification for the prediction of skeletal-related events in patients with castration-resistant prostate cancer with bone metastases.
  3. Validation of nine prognostic models in patients with bone metastases undergoing surgery.
  4. [Efficacy and safety of denosumab in the treatment of prostate cancer with bone metastases: A systematic review and meta-analysis].
  5. Predicting Bone Metastasis in Prostate Cancer Patients Using Total Serum Prostate-Specific Antigen and Serum Alkaline Phosphatase: Model Development, Validation, and Deployment as a Digital Risk Estimator.
  6. The influence of stem length on perioperative complications following cemented hip arthroplasty in metastatic femoral disease: A systematic review.
  7. Computational Assessment of Fracture Risk in Vertebral Bodies With Simulated Defects: The Role of Baseline Strength and Tumor Size.
  8. Editorial: Surgical management of spine and spinal cord metastasis.
  9. Exploring the accuracy of whole-body MRI in assessing treatment response in metastatic breast cancer: A narrative review.
  10. Artificial intelligence across the cancer care continuum.
  1. J Bone Oncol. 2025 Oct;54 100707
    Social determinants are associated with clinical presentation of acute pathological fracture in metastatic long-bone disease.
    Tom M de Groot, Lotte R van der Linden, Angad D S Bedi, Andreea A Lucaciu, Caleb C Jang, Olivier Q Groot, Job N Doornberg, Paul C Jutte, Santiago A Lozano-Calderon, J H Schwab.
       Background: Social Determinants of Health (SDOH) are non-medical factors that influence health, which have gained recognition across medical disciplines. Their impact on survival and disease presentation of patients with metastatic bone disease (MBD) remains unexplored.
    Methods: This retrospective observational study included 712 undergoing surgery for symptomatic long-bone metastases patients between 2013 and 2022. SDOH were evaluated using Cox Proportional hazards regression for post-operative survival. A multivariate logistic regression analysis was performed to identify associated factors for clinical presentation with a completed pathologic fracture.
    Results: The median overall survival was 264 days (IQR 74-772). Clinical presentation with a pathologic fracture as the initial symptom of metastatic bone disease (MBD) was observed in 15 % of patients (106/712).SDOH factors played a significant role in clinical presentation. Patients with secondary insurance coverage were substantially less likely to present with a pathologic fracture (OR 0.26, 95 % CI 0.14-0.49; p < 0.01). In a sub-analysis of the most common tumors (breast, renal, and lung cancer patients; n = 353), attending college was associated with a significantly lower likelihood of presenting with a pathologic fracture as the initial symptom of metastatic bone disease (OR 0.54, 95 % CI 0.30-0.95; p = 0.03).
    Conclusion: This study suggests that unfavorable SDOH factors are associated with decreased post-operative survival and a higher likelihood of initial clinical presentation with a completed pathological fracture. Incorporating social determinants into comprehensive care strategies for individuals with MBD may guide targeted interventions and optimize patient management to improve outcomes.
    Keywords:  Long-bone; Metastatic long-bone disease; Pathologic fractures; Social determinants; Survival
    DOI:  https://doi.org/10.1016/j.jbo.2025.100707
  2. PLoS One. 2025 ;20(8): e0328792
    Risk stratification for the prediction of skeletal-related events in patients with castration-resistant prostate cancer with bone metastases.
    Masanori Hamada, Eiji Nakata, Ryuichi Nakahara, Shinsuke Sugihara, Haruyoshi Katayama, Takuto Itano, Tomohiro Inoue, Shota Takihira, Yoshiteru Akezaki, Toshifumi Ozaki.
      Skeletal-related events (SREs) are common in patients with bone metastases from castration-resistant prostate cancer (CRPC). Despite advances in prostate cancer treatment, clinically validated predictive models for SREs in CRPC patients with bone metastases remain elusive. This gap in prognostic tools hinders optimal patient management and treatment planning for this high-risk population. This study aimed to develop a prediction model for SRE by investigating potential risk factors and classifying them into different groups. This model can be used to identify patients at high risk of SREs who need close follow-up. Between 2004 and 2013, 68 male patients with bone metastases from CRPC who were treated at our institute were evaluated for survival without SREs and survival without SREs of the spinal cord. The study analyzed clinical data at enrollment to identify risk factors for initial and spinal SREs. Multivariate analysis revealed that a high count of metastatic vertebrae, along with visceral or lymph node metastases, were significant risk factors. Patients were categorized into four subgroups based on the number of vertebral metastases and presence of visceral or lymph node metastases: 1) extensive vertebral and both types of metastases, 2) extensive vertebral without additional metastases, 3) some vertebral with other metastases, 4) some vertebral without additional metastases. The first SRE and spinal SRE occurred significantly sooner in the first subgroup compared to others. Incidence rates at 12 months for the first SRE were 56%, 40%, 27%, and 5%, and for the first spinal SRE were 47%, 40%, 27%, and 0% respectively. Patients with extensive vertebral and additional metastases require vigilant monitoring to mitigate SREs.
    DOI:  https://doi.org/10.1371/journal.pone.0328792
  3. J Orthop Surg Res. 2025 Aug 11. 20(1): 754
    Validation of nine prognostic models in patients with bone metastases undergoing surgery.
    Maria A Smolle, Philip Elmer, Florian A Wenzl, Lukas Leitner, Peter Ferlic, Susanne Scheipl, Patrick Sadoghi, Andreas Leithner.
       BACKGROUND: We aimed to 1) assess the prognostic performance of established prediction models for mortality in patients with spine and extremity bone metastases, 2) evaluate their performance in clinically relevant subgroups, and 3) study the importance of relevant patient characteristics for mortality prediction.
    METHODS: Between 29th May, 2000 and 21st April, 2022, a total of 526 patients (median age 67.0 years, interquartile range [IQR] 58.1 - 74.0 years], 271 males; median follow-up 267 days [IQR 86 - 856 days]) undergoing surgery for spine or extremity bone metastases were retrospectively included. Nine prognostic models were evaluated in the entire cohort (n = 526), and separately in subgroups treated for spine (n = 224) or extremity (n = 302) metastases. Cox-regression and logistic regression models were used, as appropriate. Harrell's c-statistic, the area under the receiver operating characteristic curve (AUC ROC) and Brier score were used as performance metrics.
    RESULTS: When assessed in the entire cohort, models by Sorensen et al. (AUC 12 months 0.834), Janssen et al. (c-index 0.711) and Katagiri et al. (c-index 0.699) achieved highest discriminatory performance. Likewise, all three models performed best when studied in the spine subgroup (Sorensen et al.: AUC 12 months 0.826; Janssen et al.: c-index 0.723; Katagiri et al.: c-index 0.717), although the models by Sorensen et al. and Janssen et al. had been developed for patients with extremity metastasis. Performance of all models was slightly lower when assessed in the extremity subgroup. Haemoglobin levels and tumour profile (i.e. primary histology) ranked among the most important predictors, consistent across subgroups.
    CONCLUSIONS: Our study suggests particularly helpful predictive performance of the models by Sorensen et al. and Janssen et al. in both patients with extremity metastases and patients with spine metastases undergoing surgery. Given that we only included patients undergoing surgery, additional validation studies in conservatively treated patients are warranted.
    Keywords:  Bone metastasis; Extremity metastasis; Outcome; Prognostic scoring model; Spine metastasis
    DOI:  https://doi.org/10.1186/s13018-025-06147-7
  4. Zhonghua Nan Ke Xue. 2025 Apr;31(4): 349-356
    [Efficacy and safety of denosumab in the treatment of prostate cancer with bone metastases: A systematic review and meta-analysis].
    Li Yang, Bo Fang, Can-Qin He, Xu-Xin Zhan, You-Ping Xiao, Xiao-Jun Qin, Qiang Lou, Xue-Jun Shang.
       OBJECTIVE: To evaluate the efficacy and safety of denosumab in the treatment of prostate cancer with bone metastases.
    METHODS: Relevant studies were retrieved from PubMed, EMBASE, Cochrane, Web of Science, Sinomed , CNKI and Wanfang databases. The Cochrane risk-of-bias assessment tool was used to evaluate the quality of included studies, and relevant data were extracted. meta-analysis was performed using RevMan 5.4 and RStudio software, and forest plots were generated.
    RESULTS: Six randomized controlled trials (RCTs) were included. Compared with the control group, denosumab significantly reduced the risk of skeletal-related events (HR=0.78, 95% CI: 0.62-0.93). In terms of safety, denosumab did not increase the risk of total adverse events, severe adverse events and the adverse events higher than CTC grade 3.
    CONCLUSION: Denosumab can delay the time to first skeletal-related event with good safety. However, due to the limitations of this study, further high-quality, large-sample, multicenter RCTs are needed to confirm these findings.
    Keywords:   denosumab; prostate cancer with bone metastasis; meta-analysis; systematic review; randomized controlled trial
  5. Cureus. 2025 Jul;17(7): e87786
    Predicting Bone Metastasis in Prostate Cancer Patients Using Total Serum Prostate-Specific Antigen and Serum Alkaline Phosphatase: Model Development, Validation, and Deployment as a Digital Risk Estimator.
    Frank Obeng, Alfred Yawson, Nii-Boye Hammond, Sylvester A Boakye, Banabas Kpankyaano, Appiateng W Boadu, Evans K Zikpi, Justice Dzomeku, Dominic A Dankwah, James E Mensah.
      Introduction This study addresses the global controversy over routine bone scans for newly diagnosed prostate cancer patients, focusing on the Ghanaian population. It aims to assess the predictive value of prostate-specific antigen (PSA) for bone metastasis and the role of serum alkaline phosphatase (ALP) in enhancing prediction. Methods This study was conducted at Korle Bu Teaching Hospital over 14 months and included 258 treatment-naïve prostate cancer patients. Clinical evaluation, PSA and ALP tests, and technetium-99 bone scans were performed. Chi-square and t-tests identified significant predictors of bone metastasis. The predictors were regressed logistically into a model, which was validated, trained, updated, and programmed into a digital risk calculator. All analysis was at a 0.05 significance level. Findings The mean age of participants was 68.18 ± 7.34 years (68.83 and 67.77 years for the metastatic and non-metastatic groups, respectively). Increasing PSA (OR=4.59, p<0.001), ALP (OR=4.24, p<0.001), DRE risk group (OR=1.60, p<0.05), and International Society of Urological Pathology (ISUP) (OR=1.72, p<0.05) were associated with increasing risk of bone metastasis. A two-unit rise along the D-Amico risk strata was associated with a 28-fold increase in the odds of metastasis (low risk vs high risk, OR=29.56, p<0.001; low risk vs intermediate risk, OR=2.80, p=0.368). Among participants with more than 30% of their core-biopsy volume involved with adenocarcinoma, 54.0% had bone metastasis (OR=1.33, p=0.06). Also, 57% of those with perineural invasion had bone metastasis (OR=4.0, p=0.01). Perivascular invasion was not a statistically significant predictor (p=0.346). All patients with cribriform pattern histology had bone metastasis (100%; OR=9.40, p=0.04). Of those with bone pain, 48.4% had bone metastasis (OR=2.25, p=0.002). PSA and ALP exhibited strong independent associations with bone metastasis, with PSA outperforming other predictors (AUC under ROC curve of 81.65% vs 77.97% for ALP, 69.73% for DRE, and 79.19% for ISUP. On multivariate logistic regression, the combined AUC for PSA and ALP was 89.28%, while that for combined PSA, ALP, DRE, and ISUP was 92.3%). A PSA cut-off of 18.95 ng/mL or an ALP cutoff of 59.48 IU/L, individually, detected 97.5% of bone metastasis. Combining a PSA cut-off of 20.85 ng/mL with an ALP cut-off of 44.0 IU/L yielded a 100% detection rate, while PSA above 20 ng/mL, DRE >T2c, and Gleason score >7 predicted 95% of bone metastasis in this cohort. In a logistic regression model, ALP, ISUP, and DRE stage significantly improved the bone metastasis detection rate of PSA in prostate cancer (z-statistic gain at p=0.05 was 2.41; new AUC=92.29%). The inclusion of bone pain, cribriform pattern histology, perineural invasion, and percentage core involvement of adenocarcinoma yielded just marginal gains (maximum z-statistic gain at p=0.05 was 0.61; new AUC: 93.90%). Conclusion For high-risk prostate cancer, bone scans are recommended. In Ghana, a PSA cut-off of 18.95 ng/mL could safely exclude 20% of bone scans, missing only 2.5% of bone metastases, saving $170 per patient ($55,000 nationally per year). Combining this with an ALP cut-off of 44.0 IU/L (0% false-negative rate) detects 100%. A validated risk model combining PSA, ALP, ISUP, and DRE achieves an AUC of 92.3%, sensitivity of 89.9%, specificity of 78.8%, and accuracy of 85.6%, offering a practical, digitally deployed, decision support tool.
    Keywords:  alkaline phosphatase; bone metastasis; clinical decision support tools; digital risk-estimator of bone metastasis in prostate cancer; dre stage; gleason score (isup grade); logistic regression model; prostate-specific antigen; technetium-99 bone scan
    DOI:  https://doi.org/10.7759/cureus.87786
  6. J Orthop. 2025 Oct;68 276-282
    The influence of stem length on perioperative complications following cemented hip arthroplasty in metastatic femoral disease: A systematic review.
    Joseph D Giacalone, Jared Garfinkle, Surabhi Panda, Jason Abraham, Kassandra Parrales, Christopher Haydel.
       Introduction: Long stem cemented hip arthroplasty remains a common surgical treatment for metastatic disease to the proximal femur. However, long stems may increase the risk of cardiopulmonary complications due to embolic events. This study presents the first systematic review directly comparing perioperative complication rates between long and short/standard cemented femoral stems in this patient population.
    Methods: A systematic search of PubMed, EMBASE, Web of Science, and Cochrane Library was conducted in accordance with PRISMA guidelines. Studies were included if they reported on cemented hip arthroplasty for proximal femoral metastases, defined femoral stem length (short/standard: <250 mm vs. long: ≥250 mm), and described perioperative cardiopulmonary complications.
    Results: Seven studies met inclusion criteria, encompassing 379 femurs (160 short/standard stems and 219 long stems). Patients who received long-stem constructs had significantly higher rates of total perioperative cardiopulmonary complications (26.0 % vs. 3.1 %). Total complication rates were also higher in the long-stem group (28.8 % vs. 10.6 %). Only five cases (1.3 %) of new distal metastatic lesions were reported.
    Conclusion: Long cemented femoral stems are associated with higher perioperative complication rates than short or standard stems in patients undergoing hip arthroplasty for proximal femoral metastases. Given the low observed incidence of new distal lesions, the rationale for routinely using long stems warrants reconsideration. Future prospective studies should adopt standardized definitions for cardiopulmonary complications and stem length, report BCIS using validated criteria, and evaluate the true incidence of new distal metastases to guide surgical decision-making in this high-risk population.
    Keywords:  Cemented hip arthroplasty; Hip arthroplasty; Metastatic bone disease; Perioperative complications; Proximal femur; Systematic review
    DOI:  https://doi.org/10.1016/j.jor.2025.07.029
  7. Int J Numer Method Biomed Eng. 2025 Aug;41(8): e70081
    Computational Assessment of Fracture Risk in Vertebral Bodies With Simulated Defects: The Role of Baseline Strength and Tumor Size.
    Mehran Fereydoonpour, Asghar Rezaei, Areonna Schreiber, Lichun Lu, Mariusz Ziejewski, Ghodrat Karami.
      Accurately predicting vertebral fracture risk in metastatic spines remains a critical challenge in clinical practice. This study developed and validated a QCT-based finite element analysis (QCT/FEA) approach to investigate the combined effects of baseline bone strength and tumor size on vertebral structural integrity. Areal bone mineral density (aBMD) was also calculated from QCT data to evaluate the reduction in bone density with increasing defect size. Nine cadaveric vertebral bodies were analyzed under varying tumor sizes (0%, 20%, 35%, and 50%). The results demonstrated a strong correlation between experimentally measured and computationally predicted failure forces (r = 0.97, p < 0.001) and aBMD values (r = 0.96, p < 0.001). Vertebral strength decreased linearly with increasing tumor size. Importantly, the study revealed that baseline vertebral strength plays a crucial role in fracture risk assessment, often surpassing the impact of tumor size alone. Tumor size reduced vertebral strength at a rate 84% faster than bone density (p = 0.009), highlighting a greater impact of tumor defects on bone fracture force than on bone density. These findings suggest that relying solely on tumor size for fracture risk prediction may be insufficient. Incorporating baseline bone strength into predictive models significantly enhances accuracy and reliability, providing valuable insights for clinical decision-making and personalized treatment strategies. This study underscores the importance of advanced computational tools in improving vertebral fracture risk assessment in metastatic spine cases.
    Keywords:  defect size; finite element analysis; metastatic spine; vertebral fracture
    DOI:  https://doi.org/10.1002/cnm.70081
  8. Front Neurol. 2025 ;16 1639941
    Editorial: Surgical management of spine and spinal cord metastasis.
    Rouzbeh Motiei-Langroudi, Efstathios Papavassiliou, Andrew Grossbach, Ryan C Hofler.
      
    Keywords:  multidisciplinary treatment; radiation; spinal cord metastasis; spine metastasis; surgery
    DOI:  https://doi.org/10.3389/fneur.2025.1639941
  9. Radiography (Lond). 2025 Aug 08. pii: S1078-8174(25)00243-3. [Epub ahead of print] 103099
    Exploring the accuracy of whole-body MRI in assessing treatment response in metastatic breast cancer: A narrative review.
    S Murali, W Sz-Ying Lee, L H Wei-En, C J Yi Samuel, J T Ann Tan, B Jia Wei, J O Si Pin, S Neves, S Okoli, O Okoli, S Adeleke.
       OBJECTIVES: Breast cancer is the second most common cancer worldwide, with metastasis leading to significant morbidity, mortality and healthcare costs. Bone metastasis remains particularly prevalent, estimated to appear in 70 % of cases. Therefore, accurate monitoring of treatment response in metastatic breast cancer is critical.
    KEY FINDINGS: In this review, we advocate for the use of whole-body MRI, which has emerged as a promising alternative to more typical modalities such as CT, PET-CT and bone scintigraphy; this is owed to its high diagnostic accuracy without the need for ionizing radiation or intravenous contrast agents. However, we do acknowledge that challenges persist due to a lack of standardized breast whole body MRI protocols, image reporting criteria, costs, and accessibility issues, limiting its broader implementation.
    CONCLUSIONS: Despite these challenges, MRI's capabilities are expanding, with further research required to establish standardized protocols and validate its use in diverse populations to reinforce whole-body MRI as a preferred imaging modality in metastatic breast cancer.
    IMPLICATIONS FOR PRACTICE: While the future is promising for whole-body MRI, further studies and research will help strengthen the literature base for wider implementation of this modality in regular clinical practice.
    Keywords:  Magnetic resonance imaging; Metastatic breast cancer; Treatment response
    DOI:  https://doi.org/10.1016/j.radi.2025.103099
  10. Cancer. 2025 Aug 15. 131(16): e70050
    Artificial intelligence across the cancer care continuum.
    Irbaz Bin Riaz, Muhammad Ali Khan, Travis J Osterman.
      Artificial intelligence (AI) holds significant potential to enhance various aspects of oncology, spanning the cancer care continuum. This review provides an overview of current and emerging AI applications, from risk assessment and early detection to treatment and supportive care. AI-driven tools are being developed to integrate diverse data sources, including multi-omics and electronic health records, to improve cancer risk stratification and personalize prevention strategies. In screening and diagnosis, AI algorithms show promise in augmenting the accuracy and efficiency of medical image analysis and histopathology interpretation. AI also offers opportunities to refine treatment planning, optimize radiation therapy, and personalize systemic therapy selection. Furthermore, AI is explored for its potential to improve survivorship care by tailoring interventions and to enhance end-of-life care through improved symptom management and prognostic modeling. Beyond care delivery, AI augments clinical workflows, streamlines the dissemination of up-to-date evidence, and captures critical patient-reported outcomes for clinical decision support and outcomes assessment. However, the successful integration of AI into clinical practice requires addressing key challenges, including rigorous validation of algorithms, ensuring data privacy and security, and mitigating potential biases. Effective implementation necessitates interdisciplinary collaboration and comprehensive education for health care professionals. The synergistic interaction between AI and clinical expertise is crucial for realizing the potential of AI to contribute to personalized and effective cancer care. This review highlights the current state of AI in oncology and underscores the importance of responsible development and implementation.
    Keywords:  artificial intelligence (AI); cancer screening; cancer survivorship; end‐of‐life care; medical oncology; radiation oncology; surgical oncology
    DOI:  https://doi.org/10.1002/cncr.70050
This page is being maintained by Thomas Krichel. It was last updated on 2025‒08‒17 at 8:22.