bims-rebome 2025-09-28 papers

Cancer Med. 2025 Sep;14(18): e71201

Do Race, Insurance Status, and Income Factors Impact Pathologic Fracture Presentation and Management?

Ashley B Bozzay, Kara Churovich, Julio A Rivera, Benjamin K Potter.

INTRODUCTION: Metastatic bone disease (MBD) and pathologic fractures (PF) can impact quality of life, functionality, and survival. Understanding the management of PF and access to care and treatment in the U.S. healthcare system can improve patient outcomes, directly impacting treatment eligibility and overall survival. We ask: (1) Do race, income, and insurance status differ between prophylactic stabilization of impending and acute fixation of overt PF, respectively? (2) Are race, income, and insurance status associated with complications in patients with metastatic bone disease? (3) Are race, income, and insurance associated with length of stay and insurance type in patients with MBD?
METHODS: The NIS HCUP database was queried from 2016 to 2020 for pathological fractures. We then identified patients with associated cancer ICD-10 diagnostic codes for the hospitalization (breast, prostate, renal, lung, thyroid, bone, and other). General linear models (GLMs) were used to answer each clinical question. We conducted a post hoc analysis of the other malignancies associated with osseous metastasis and performed the same studies as above.
RESULTS: We found 2050 prophylactically stabilized impending and 4181 acute fractures. There were no differences among races, income, or insurance status and the prevalence of impending versus acute fractures. We found that Black patients were more likely to have complications, while Hispanic patients were the least likely, compared to other races. Black patients had higher hospital costs, while both Black and Hispanic patients had more extended hospitalizations and were more likely to have Medicaid or no insurance compared to other races. Our post hoc analyses found that the rate of impending and acute fractures differed among race, income, and insurance status, depending on the metastatic cause.
CONCLUSIONS: We identified healthcare disparities in patients with impending and overt PF due to MBD despite minimal to no differences in patient comorbidities, fracture management, or hospitalization complications.

Keywords: care management; metastatic bone disease; pathological fracture; socioeconomic factors

DOI: https://doi.org/10.1002/cam4.71201

Spine J. 2025 Sep 19. pii: S1529-9430(25)00786-7. [Epub ahead of print]

Prognostic Outcomes of Spinal Metastasis: Timing of Metastasis Presentation Matters.

Shan-Lun Tsao, Chang-Wei Tsou, Yu-Ting Pan, Hung-Kuan Yen, Hao-Chen Lin, Jen-Hao Liu, Fon-Yih Tsuang, Ue-Cheung Ho, Wei-Hsin Lin, Ming-Hsiao Hu, Paul Ogink, Olivier Q Groot.

BACKGROUND CONTEXT: Spinal metastasis (SM), though typically associated with late-stage disease, can manifest at any point in the disease process as a synchronous spinal metastasis (SSM) or metachronous spinal metastasis (MSM). The timing of SM presentation can influence the complexity of treatment approaches. Therefore, investigating the clinical and prognostic distinctions between SSM and MSM is vital for enhancing patient management strategies.
PURPOSE: This study investigates the incidence, prognosis, and primary malignancies differences between SSM and MSM, aiming to improve clinical practice through inclusion of both surgical and/or radiotherapy cases.
STUDY DESIGN/SETTING: A retrospective study at a single tertiary care center in Taiwan PATIENT SAMPLE: 4269 patients aged 18 or older who received surgery and/or radiotherapy for image-confirmed spinal metastasis at a tertiary medical center in Taipei from 2010 to 2022 OUTCOME MEASURES: The primary outcome was the incidence of SSM among patients with SM requiring local treatment. Secondary outcomes included survival differences and primary malignancy distributions between SSM and MSM.
METHODS: SSM was defined as SM diagnosed within 31 days of initial cancer diagnosis; MSM was diagnosed later. Missing data was handled with multiple imputation using chained equations. Prognostic differences were analyzed using univariate and multivariate Cox proportional hazards models, and survival outcomes were compared with Kaplan-Meier and log-rank tests. Differences in primary malignancy types and growth rates were evaluated using Chi-square test or Fisher's exact test.
RESULTS: SSM was identified in 19.6% (838/4269) and MSM in 80.4% (3431/4269). SSM patients had a longer median survival than MSM (17.4 months, interquartile ranges [IQR] 5.6-49.0 vs. 7.5 months, IQR 3.0-20.9; p<0.001). Lung cancer was the most common primary malignancy, comprising nearly half of SSM cases. Patients with SSM had a more favorable prognosis than MSM (HR=0.74; p<0.001).
CONCLUSION: One-fifth of the patients were diagnosed with SM before the primary tumor was identified. These SSM patients exhibit distinct clinical and prognostic profiles compared to MSM patients, often showing a survival advantage likely due to their treatment-naïve status and lower tumor burden at time of presentation. These differences suggest that patients with SSM may benefit from tailored treatment approaches, such as more durable surgical stabilization or consideration of higher radiation doses, given their comparatively favorable survival outlook. Future studies should recognize SSM as a unique clinical entity to refine prognostic models and optimize therapeutic approaches.

Keywords: Bone Metastasis; Outcome Prediction; Prediction; Prognosis; Spinal Metastasis; Spine

DOI: https://doi.org/10.1016/j.spinee.2025.09.002

Medicina (Kaunas). 2025 Sep 10. pii: 1637. [Epub ahead of print]61(9):

Managing Bone Metastases with Denosumab: Real-World Data and Critical Monitoring Points in Breast, Lung, and Prostate Cancers.

Sibel Oyucu Orhan, Bedrettin Orhan, Şeyma Esenbuğa, Seda Sali, Burcu Caner, Birol Ocak, Ahmet Bilgehan Şahin, Adem Deligönül, Türkkan Evrensel, Erdem Çubukçu.

Background and Objectives: Advanced solid organ tumors, particularly breast, lung, and prostate cancers, frequently metastasize to bone, leading to debilitating skeletal-related events (SREs). Denosumab, a RANKL inhibitor, is crucial in preventing SREs. This study aimed to comparatively evaluate the efficacy and adverse effect profiles of denosumab in patients with bone metastases originating from these three common cancer types. Materials and Methods: This retrospective study included 146 patients treated with denosumab for bone metastases. Data on demographics, SREs before and during denosumab treatment, serum creatinine, calcium, and magnesium levels (at baseline, 3, and 6 months), other adverse effects, and survival were analyzed. Results: Before denosumab, SREs were present in 36.3% of patients (breast: 43.4%, prostate: 28%, lung: 33.8%). During denosumab treatment, SRE rates markedly decreased across all groups (breast: 9.4%, prostate: 16.0%, lung: 8.8%), with no significant intergroup difference in on-treatment SREs. Significant decreases in serum calcium levels were observed at 3 and 6 months post-denosumab initiation in breast (p < 0.0001) and lung cancer patients (p = 0.001). Mean creatinine levels significantly decreased in lung (p < 0.0001) and prostate (p = 0.020) cancer patients at 3 and 6 months. Overall survival significantly differed, with lung cancer patients having the shortest median survival (p < 0.005). Conclusions: Denosumab effectively reduces the incidence of SREs in patients with bone metastases from breast, lung, and prostate cancer. However, clinicians must diligently monitor for hypocalcemia, a notable adverse effect, particularly at 3 and 6 months after starting denosumab, with specific caution warranted in patients with lung cancer.

Keywords: bone metastasis; denosumab; hypocalcemia; skeletal-related events

DOI: https://doi.org/10.3390/medicina61091637

J Clin Med. 2025 Sep 09. pii: 6358. [Epub ahead of print]14(18):

Ablative Techniques for the Management of Osseous Spine Metastases: A Narrative Review.

Zach Pennington, Jonathan M Morris, Aladine Elsamadicy, Sheng-Fu Larry Lo, Joseph H Schwab, Daniel M Sciubba.

With continued improvements in systemic cancer therapies, there has been an increase in the survivorship of patients with spinal metastases. However, many patients with spinal metastases are frail and may not be able to tolerate the morbidity of open surgery. For these patients, percutaneous ablation techniques offer a minimally invasive approach that can facilitate local tumor control and pain relief. Here we describe the currently employed modalities-radiofrequency ablation (RFA), microwave ablation (MWA), cryoablation, and laser interstitial thermal therapy (LITT)-summarize the clinical support for their use, and overview the relative risks and benefits for each. All these technologies offer to help improve local tumor control and improve oncologic pain associated with vertebral metastases, and they have become a staple of multidisciplinary spine metastasis care at many centers. As clinical experience with these technologies continues to grow, their use will likely become more widely adopted, and so understanding of their indications, risks, and benefits will become increasingly important to the practicing spine oncologist.

Keywords: cryoablation; epidural spinal cord compression; frailty; laser interstitial thermal therapy (LITT); microwave ablation (MWA); minimally invasive surgery; percutaneous technique; radiofrequency ablation (RFA); spine metastases

DOI: https://doi.org/10.3390/jcm14186358

Spine (Phila Pa 1976). 2025 Oct 15. 50(20): 1410-1419

Machine Learning-Based Prediction of Quality of Life Improvement After Surgery for Spinal Metastases: A Prospective Multicenter Study.

Kyota Kitagawa, Satoshi Maki, Yuki Shiratani, Akinobu Suzuki, Koji Tamai, Takaki Shimizu, Kenichiro Kakutani, Yutaro Kanda, Hiroyuki Tominaga, Ichiro Kawamura, Masayuki Ishihara, Masaaki Paku, Yohei Takahashi, Toru Funayama, Kousei Miura, Eiki Shirasawa, Hirokazu Inoue, Atsushi Kimura, Takuya Iimura, Hiroshi Moridaira, Hideaki Nakajima, Shuji Watanabe, Koji Akeda, Norihiko Takegami, Kazuo Nakanishi, Hirokatsu Sawada, Koji Matsumoto, Masahiro Funaba, Hidenori Suzuki, Haruki Funao, Tsutomu Oshigiri, Takashi Hirai, Bungo Otsuki, Kazu Kobayakawa, Koji Uotani, Koichi Sairyo, Shinji Tanishima, Ko Hashimoto, Chizuo Iwai, Daisuke Yamabe, Akihiko Hiyama, Shoji Seki, Kenji Kato, Masashi Miyazaki, Kazuyuki Watanabe, Toshio Nakamae, Takashi Kaito, Hiroaki Nakashima, Narihito Nagoshi, Satoshi Kato, Shiro Imagama, Kota Watanabe, Seiji Ohtori, Gen Inoue, Takeo Furuya.

STUDY DESIGN: A prospective multicenter cohort study.
OBJECTIVE: To develop and validate machine learning models for predicting health-related quality of life (HRQoL) improvements in patients after one month and six months of surgery for spinal metastases.
SUMMARY OF BACKGROUND DATA: The prediction of postoperative HRQoL of spinal metastases surgery remains understudied compared with studies of survival outcomes.
METHODS: We analyzed data from 413 patients who underwent surgery for spinal metastases at 40 participating institutions in Japan. The primary outcome was HRQoL improvement, defined as an increase in the EuroQol 5-Dimension 5-Level (EQ-5D) utility value of ≥0.32 from baseline. We developed two models for 1-month (n=360) and 6-month (n=189) outcomes using various machine learning algorithms. Missing values were imputed, and feature selection was performed using recursive feature elimination with cross-validation. We split the data into training (80%) and test (20%) sets for each model. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, precision, and F1-score. SHapley Additive exPlanations (SHAP) analysis was used to interpret feature importance.
RESULTS: The 6-month model outperformed the 1-month model across all metrics. For 1-month predictions, Logistic Regression achieved an AUC of 0.8136 and an accuracy of 0.7639 on the test set. For 6-month predictions, Naive Bayes demonstrated an AUC of 0.8928 and an accuracy of 0.8684. The 1-month model used 12 features, while the 6-month model required seven. SHAP analysis revealed that EQ-5D Mobility was the most influential feature in both models.
CONCLUSIONS: Our models demonstrate high predictive accuracy for HRQoL improvements following spinal metastases surgery, with superior performance of the 6-month model. These models could enhance clinical decision-making and patient counseling by providing personalized predictions of postoperative QoL. Future research should focus on external validation and integration of these models into clinical practice.

Keywords: EuroQol 5-Dimension 5-Level; SHAP analysis; Spinal Instability Neoplastic Score; Tokuhashi score; health-related quality of life; machine learning; patient-reported outcomes; postoperative outcome; prediction model; prognostic features; prospective multicenter study; spinal metastasis

DOI: https://doi.org/10.1097/BRS.0000000000005367