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
... -
《-》
Icariin promoted ferroptosis by activating mitochondrial dysfunction to inhibit colorectal cancer and synergistically enhanced the efficacy of PD-1 inhibitors.
A controlled type of cell death called ferroptosis is linked to increased reactive oxygen species (ROS), lipid peroxidation, and iron buildup. Furthermore, evidence indicates that ferroptosis may act as an immunogenic form of cell death with potential physiological functions in tumors and immunosuppression. Inducing ferroptosis in tumor cells may have the potential to complement cancer immunotherapy strategies. The development of colorectal cancer (CRC) and the poor efficacy of immunotherapy are associated with the crosstalk of cellular ferroptosis. Currently, Icariin (ICA), the main bioactive component extracted from Epimedium, has been shown to inhibit a variety of cancers. However, the specific role and potential mechanism of ICA in regulating ferroptosis in CRC remains unclear.
The aim of this investigation was to clarify the mechanism underlying the anti-CRC cancer properties of ICA and how it induces ferroptosis to enhance immunotherapy.
To evaluate cell viability, the Cell Counting Kit-8 (CCK-8) test was utilized. The transwell test and the wound healing assay were used to assess cell migration. A subcutaneous graft tumor model was constructed with C57BL/6 mice using MC38 colorectal cancer cell lines. The inhibitory effect of ICA on CRC, ferroptosis level and immunomodulatory effects were detected by serum biochemical assay, cytokine assay, hematoxylin-eosin (H&E) staining, immunofluorescence staining, CyTOF mass spectrometry flow screening and Western blotting. Western blotting, proteomics, molecular docking and microscale thermophoresis (MST) were used to forecast and confirm ICA's binding and interaction with HMGA2, STAT3, and HIF-1α. Moreover, the levels of lipid peroxidation and ferroptosis were assessed through the use of the C11-BODIPY fluorescent probe, the FerroOrange fluorescent probe, the iron level, the malondialdehyde (MDA) and reduced glutathione (GSH) assay kit, and Western blotting analysis. To assess alterations in mitochondrial structure and membrane potential, transmission electron microscopy (TEM) and JC-1 immunofluorescence were employed.
It was demonstrated in the current study that ICA treatment inhibits CRC and enhances anti-PD-1 therapy efficacy by inciting ferroptosis. As shown in vitro, ICA inhibits CRC cell proliferation, migration, and apoptosis. As demonstrated in vivo, ICA has a dose-dependent tumor suppressor effect when combined with anti-PD-1, it can significantly inhibit tumor growth, increase the expression of serum TNF-α, IFN-γ, and granzyme B, and promote CD69+CD8+ T, CD69+CD8+Tem, CD69+CD8+Teff, TCRβ+CD8+ T, TCRβ+CD8+ T, TCRβ+CD8+Tem, TCRβ+CD8+Teff. The inhibitory effect of ICA on CRC was associated with the binding of HMGA2, STAT3, and HIF-1α proteins, which inhibited CRC by increasing the levels of reactive oxygen species (ROS) and malondialdehyde (MDA), promoting the accumulation of iron (Fe2+), depletion of reduced glutathione (GSH), inhibiting SLC7A11 and GPX4 expressions, thereby inducing ferroptosis in CRC. As a consequence of ICA-induced ferroptosis, mitochondria are dysfunctional, with increased ROS production, membrane potential depolarization (MMP), and ATP production reduced. This process can be efficiently reversed by the mitochondria-targeted antioxidant Mito-Q. It is noteworthy that the ferroptosis inhibitor liproxstatin-1 (lip-1), anti-CD8, and anti-IFN-γ exhibited a significant inhibitory effect on the level of ferroptosis and antitumor capacity of ICA combined with anti-PD-1. This finding suggests that the antitumor immunopotentiating effect of ICA on anti-PD-1 is dependent on the secretion of IFN-γ-induced ferroptosis of CRC cells by the CD8+ T cell.
Our study represents the inaugural demonstration of the mechanism whereby ICA exerts anti-CRC effects and synergistically enhances the efficacy of anti-PD-1, inducing mitochondrial damage and leading to ferroptosis. ICA promotes ferroptosis of CRC cells by inducing mitochondrial dysfunction, and ICA combined with anti-PD-1 significantly promotes CD69, TCRβ signalling, activates effector CD8+ T cells to secrete IFN-γ, and achieves immunopotentiation by promoting ferroptosis of CRC cells, thus inhibiting CRC development. This study is built upon existing research into the pharmacodynamic mechanisms of ICA in the context of CRC, and offers a novel therapeutic approach in addressing the issue of CRC immunotherapy potentiation.
Haoyue W
，Kexiang S
，Shan TW
，Jiamin G
，Luyun Y
，Junkai W
，Wanli D
... -
《-》
ResearchGate
(全网免费下载)
钛学术
(全网免费下载)
