Materiały źródłowe

• #1 Outcomes of comprehensive treatment for primary osteosarcoma

  https://pmc.ncbi.nlm.nih.gov/articles/PMC7249600/

  This study aimed to evaluate the clinical features and outcomes of osteosarcoma to identify prognostic factors and determine new strategies to improve overall survival. […] The treatment of primary osteosarcoma with wide resection in our department, therefore, yielded favorable outcomes. However, improved treatment strategies are needed for pelvic and advanced cases. […] Recent studies have shown that the 5-year survival rate for primary osteosarcomas is approximately 65%70%, although a survival rate of approximately 90% has also been reported. […] Similarly, in our hospital, the event-free survival rate at 3 years was 66% and the 3-year survival rate was 73.3%, with eight of the 10 cases that were originally resectable showing good outcomes (CDF). These findings suggest that osteosarcoma has been appropriately treated by a multidisciplinary approach and is expected to be curable. […] The treatment outcomes of osteosarcoma in our institution were good. Aggressive and comprehensive treatment of osteosarcomas provides a favorable prognosis.

• #2 Identification of an early survival prognostic gene signature for localized osteosarcoma patients | Scientific Reports

  https://www.nature.com/articles/s41598-024-57527-8

  Osteosarcoma is the most prevalent bone tumor in pediatric patients. Neoadjuvant chemotherapy has improved osteosarcoma patient survival, however the 5-year survival rate for localized osteosarcoma is 75% with a 30-50% recurrence rate. We, therefore, sought to identify a prognostic gene signature which could predict poor prognosis in localized osteosarcoma patients. Using the TARGET osteosarcoma transcriptomic dataset, we identified a 13-hub gene signature associated with overall survival and time to death of localized osteosarcoma patients, with the high-risk group showing a 22% and the low-risk group showing 100% overall survival. […] Our data point to the Hedgehog signaling pathway as a candidate druggable cascade to improve outcomes for high-risk non-metastatic patients. […] Our 963 gene signature for localized osteosarcoma prognosis resulted in a 46.6% 5-year OS and 23.3% 10-year OS in the high-risk group, while the 5-year OS was 100% and 10-year OS 87.5% for the low-risk group.

• #3 A novel classification predicts prognosis and drug sensitivity in osteosarcoma based on alterations in gene sets | Aging

  https://www.aging-us.com/article/205614/text

  Osteosarcoma is a cancer originating in the bone cells, specifically in the osteoblasts. […] We identified a model consisting of four signaling pathways that predict the prognosis and the immune status of the tumor microenvironment and drug sensitivity in osteosarcoma patients. The novel classification may be used in clinical applications to predict prognosis and drug sensitivity. […] The prognosis for osteosarcoma has improved significantly over the years, thanks to advances in treatment strategies. Factors influencing prognosis include the size and location of the tumor, the presence of metastasis, the response to chemotherapy, and the patients overall health. With appropriate treatment, the five-year survival rate for localized osteosarcoma is around 6075%, but it decreases to approximately 1530% if metastasis has occurred.

• #4 Prognostic factors in osteosarcoma: A study level meta-analysis and systematic review of current practice

  https://pmc.ncbi.nlm.nih.gov/articles/PMC7047183/

  A consensus has not yet been reached regarding the abilities of gender, age, tumor size, tumor location, histologic subtypes, and surgery in the prediction of survival in osteosarcoma. […] Results indicated that gender (male vs. female: 1.21, 95% CI, 1.111.32; female vs. male: 0.85, 95% CI, 0.750.98), age (1220 vs. 12: 1.37, 95% CI, 1.131.65; 20 vs. 20: 1.29, 95% CI, 1.081.55; 40 vs. 40: 1.63, 95% CI, 1.212.20; 50 vs. 25: 2.60, 95% CI, 1.923.53; 60 vs. 60: 1.11, 95% CI, 1.061.18), tumor location (non-extremities vs. extremities: 2.10, 95% CI, 1.762.51; proximal vs. distal femur: 3.68, 95% CI: 1.518.96; proximal vs. distal humerus: 3.15, 95% CI: 1.536.49), tumor size (5 vs. 5: 1.42, 95% CI, 1.091.86; 8 vs. 8: 1.55, 95% CI, 1.072.24; 9 vs. 9: 1.44, 95% CI, 1.051.96), chemotherapy response (poor vs. good: 2.45, 95% CI, 2.022.97; good vs. poor: 0.41, 95% CI, 0.340.48), and surgery (yes vs. no: 0.45, 95% CI, 0.360.57; amputation vs. salvage: 2.34, 95% CI, 1.473.74) were significantly associated with overall survival in osteosarcoma patients.

• #5 Prognostic factors in osteosarcoma: A study level meta-analysis and systematic review of current practice

  https://pmc.ncbi.nlm.nih.gov/articles/PMC7047183/

  The meta-analysis demonstrated that male patients, older age, large tumor size, non-extremity osteosarcoma, proximal osteosarcoma, poor chemotherapy response, no surgical treatment, and amputation surgery were correlated with a poor prognosis in osteosarcoma patients. […] The results of the present study suggest that male gender, older age, larger tumor size, non-extremity osteosarcoma, proximal osteosarcoma, poor histological response to chemotherapy (90% necrosis), no surgical treatment, and amputation surgery are potentially responsible for the poor OS of patients with osteosarcoma.

• #6 Prediction of Neoadjuvant Chemotherapy Response in Osteosarcoma Using Convolutional Neural Network of Tumor Center 18F-FDG PET Images

  https://www.mdpi.com/2075-4418/11/11/1976

  Therefore, predicting the histological response to NAC and determining whether to maintain treatment is important for managing osteosarcoma patients. […] Tumor necrosis rate is a criterion for evaluating the chemotherapy response evaluation and has been evaluated as the most important prognostic factor in osteosarcoma, but it has a limitation that was hard to predict before NAC and can be evaluated only in the resected specimen after completing NAC. […] Recent studies with osteosarcoma patients reported that metabolic tumor volume (MTV) and total lesion glycolysis (TLG) obtained from 18F-FDG PET after one cycle of chemotherapy can predict the response of chemotherapy. […] However, in these studies, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) obtained from 18F-FDG PET prior to chemotherapy could not predict the response of chemotherapy. […] In this study, the NAC prediction model was estimated using image texture features of 18F-FDG PET images from osteosarcoma patients before and after NAC with the machine learning and deep learning algorithm.

• #7 Azthena logo with the word Azthena

  https://www.news-medical.net/health/Osteosarcoma-Prognosis.aspx

  The survival prognosis for people with osteosarcoma is estimated according to the severity of the tumor in the bone. […] The prognosis for individuals with Stage I is excellent at 90% with wide resection. […] The prognosis of Stage II osteosarcoma varies greatly, due to the large differences that may be possible between tumors of this stage. […] The longer the time to metastases, the better the prognosis will become. […] The best prognosis involves two or fewer metastatic nodules with a length of time greater than 24 months. […] The degree of necrosis after treatment with neoadjuvant chemotherapy is also indicative of prognosis. […] the prognosis is usually not very promising, with an approximate overall survival rate for this stage of 30%.

• #8 Identification of an early survival prognostic gene signature for localized osteosarcoma patients | Scientific Reports

  https://www.nature.com/articles/s41598-024-57527-8

  The combined 13 genes, however, resulted in a stronger correlation with both vital status (p=2e-5) and relapse (p=1.5e-4) compared to any single gene and comparable to the full localized survival or relapse gene signatures. […] The 13 gene signature was significantly correlated with time to death in the localized patients (p=0.048). […] These results suggest that the 13 genes could act as surrogate markers of the broader gene alterations noted in the overall survival localized gene signature. […] Our 13 gene hub signature, however, is more effective in identifying localized patients with poor prognosis within both 3- and 5- years of diagnosis.

• #9 Meta-analysis showing that ERCC1 polymorphism is predictive of osteosarcoma prognosis | Oncotarget

  https://www.oncotarget.com/article/19370/text/

  To investigate correlations between excision repair cross-complementation group 1 (ERCC1) and 2 (ERCC2) polymorphisms and osteosarcoma prognosis, we conducted a meta-analysis of studies published through October 2016. […] Our results suggest that ERCC1 rs11615 CC is associated with a better clinical outcome. This suggests rs11615 may be a useful genetic marker for predicting osteosarcoma prognosis. […] Of the four SNPs studied, only ERCC1 rs11615 was associated with improved patient OS and TR. […] In conclusion, our meta-analysis indicated that ERCC1 rs11615 is associated with improved osteosarcoma prognosis. Additional studies with larger sample sizes are needed to more precisely estimate the correlation between ERCC polymorphisms and osteosarcoma prognosis.

• #10 Multi-omics analysis identifies osteosarcoma subtypes with distinct prognosis indicating stratified treatment | Nature Communications

  https://www.nature.com/articles/s41467-022-34689-5

  Osteosarcoma (OS) is a primary malignant bone tumor that most commonly affects children, adolescents, and young adults. […] Through unsupervised integrative clustering of the multi-omics data, we classify OS into four subtypes with distinct molecular features and clinical prognosis: (1) Immune activated (S-IA), (2) Immune suppressed (S-IS), (3) Homologous recombination deficiency dominant (S-HRD), and (4) MYC driven (S-MD). […] Our comprehensive integrated characterization provides a valuable resource that deepens our understanding of the disease, and may guide future clinical strategies for the precision treatment of OS. […] However, further progress in 5-year survival has been appreciably unchanged over the past four decades and therapeutic approaches are urgently needed. […] Our study provides insight into the biology of this disease, and potential avenues for future precision medicine approaches within OS.

• #11 Multi-omics analysis identifies osteosarcoma subtypes with distinct prognosis indicating stratified treatment | Nature Communications

  https://www.nature.com/articles/s41467-022-34689-5

  The influence of age, sex, tumor position, Enneking stage and pathological type on clinical prognosis was analyzed. […] The clinical features and mutation profile of genes related to genome maintenance, oncogene/tumor suppressor gene (Oncogene/TSG), cell cycle, epigenetic and transcriptional regulation are shown. […] The majority of the single platform clusters concentrated preferentially in one of the four integrated iClusters with p<0.01, lending confidence that the integrative subtyping strategies captured the main features of each platform. [...] We further tested the clinical relevance of the integrative subtyping, and the results indicated that the four subtypes significantly differed in clinical prognosis (log rank, p=0.03). [...] We identified that patients in S-MD subtype displayed the lowest tumor necrosis rate corresponding to the worst clinical prognosis.

• #12 Multi-omics analysis identifies osteosarcoma subtypes with distinct prognosis indicating stratified treatment | Nature Communications

  https://www.nature.com/articles/s41467-022-34689-5

  These findings revealed that mitochondria-related OXPHOS was positively associated with unfavorable prognosis, which may be associated with CDDP chemoresistance. […] The combination of ICIs and anti-VEGF therapy has entered the clinic, indicating the potential benefit from this drug combination strategy for iCluster 12 patients. […] This suggests that patients in iCluster3 may be preferentially considered for DNA-damaging chemotherapy. […] Our study highlights the significant roles of MYC in iCluster4 during OS progression.

• #13 Plasma microRNA signatures predict prognosis in canine osteosarcoma patients | PLOS One

  https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0311104

  Plasma microRNA signatures predict prognosis in canine osteosarcoma patients. Appendicular central osteosarcoma (OSA) is a common and highly aggressive tumour in dogs. Metastatic disease to the lungs is common and even with chemotherapy the prognosis is generally poor. However, few cases survive well beyond reported median survival times. Current methods, including histologic grading schemes, have fallen short in their ability to predict clinical outcome. […] High expression of miR-214-3p alone was also a predictor of shorter overall survival and disease-free interval across all populations. In both multiple miRNA and multiple variable models, miR-214-3p was always the first decision point with high expression consistently predicting a worse prognosis. […] MiR-214-3p is clearly an important prognostic predictor of canine OSA in plasma as supported by previous studies and across our multiple sample populations.

• #14 Plasma microRNA signatures predict prognosis in canine osteosarcoma patients | PLOS One

  https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0311104

  MiR-214-3p was the only statistically significant miRNA to similarly stratify all three populations into high and low expressing groups for DFI and overall survival. High expression of miR-214-3p in plasma was predictive of a shorter median survival time. […] Overall, OVC1 and OVC2 shared the most single miRNAs associated with predicting clinical outcome parameters. […] MiR-214-3p levels in plasma were a diagnostic and prognostic marker for canine patients with appendicular OSA. This miRNA was also a crucial determinant in all multi-miRNA and multi-variable models. This refined the models for prediction of clinical outcome.

• #15 Initial Metabolic Tumor Volume Measured by 18F-FDG PET/CT Can Predict the Outcome of Osteosarcoma of the Extremities | Journal of Nuclear Medicine

  https://jnm.snmjournals.org/content/54/10/1725

  We evaluated the ability of metabolic and volumetric parameters measured by pretreatment 18F-FDG PET/CT to predict the survival of patients with osteosarcoma of the extremities. […] Of the imaging parameters, MTV at the fixed standardized uptake value threshold of 2.0 (MTV(2.0)) most accurately predicted metastasis by receiver-operating-characteristic curve analysis (area under the curve = 0.679, P = 0.011). […] By multivariate analysis, MTV(2.0) 105 mL (relative risk, 3.93; 95% confidence interval, 1.559.92) and poor response to neoadjuvant chemotherapy (relative risk, 4.83; 95% confidence interval, 1.6414.21) independently shortened metastasis-free survival (P = 0.004 for both parameters). […] The stratification of patients by the combined criteria of MTV(2.0) and histologic response predicted outcome in more detail.

• #16 Initial Metabolic Tumor Volume Measured by 18F-FDG PET/CT Can Predict the Outcome of Osteosarcoma of the Extremities | Journal of Nuclear Medicine

  https://jnm.snmjournals.org/content/54/10/1725

  MTV is an independent predictor of metastasis in patients with osteosarcoma of the extremities. […] The combination of MTV and histologic response predicts survival more accurately than the chemotherapeutic response alone. […] The results of this study suggest that a fixed SUV threshold of 2.0 is suitable for measuring MTV, which reflects the biologically active tumor burden in patients with osteosarcoma. […] Stratification of patients by the combined criteria of MTV and histologic response could provide more detailed prediction of clinical outcome than MTV or histologic response alone. […] The present study suggests that MTV is a better predictor of survival than the tumor size or tumor volume measured by MR imaging. […] The MTV before neoadjuvant chemotherapy can accurately predict the clinical outcomes of patients with osteosarcoma. The combination of MTV and histologic response predicts survival more accurately than the histologic response alone.

• #17 Metastasis risk prediction model in osteosarcoma using metabolic imaging phenotypes: A multivariable radiomics model | PLOS One

  https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0225242

  Osteosarcoma (OS) is the most common primary bone tumor affecting humans and it has extreme heterogeneity. Despite modern therapy, it recurs in approximately 30-40% of patients initially diagnosed with no metastatic disease, with the long-term survival rates of patients with recurrent OS being generally 20%. Thus, early prediction of metastases in OS management plans is crucial for better-adapted treatments and survival rates. […] The multivariable logistic regression model was developed using two radiomics features, SUVmax and GLZLM-SZLGE. […] The SUVmax and GLZLM-SZLGE from metabolic imaging phenotypes are independent predictors of metastasis risk assessment. They show the association between 18F-FDG-PET and metastatic colonization knowledge. The multivariable model developed using them could improve patient outcomes by allowing aggressive treatment in patients with high metastasis risk.

• #18 Metastasis risk prediction model in osteosarcoma using metabolic imaging phenotypes: A multivariable radiomics model | PLOS One

  https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0225242

  The developed multivariable logistic model with these predictors was suggested as a good fit model without overdispersion after a Hosmer-Lemeshow goodness of fit test and overdispersion evaluation. After the finalized multivariable logistic model was trained and validated using the 10-folds cross-validation method, it was applied to the test dataset. For this predictive model, good evaluation results were obtained: AUC, accuracy, and specificity were 0.8, 0.81, and 0.88, respectively. The sensitivity (0.63) was lower than other values, although it was fair. […] The findings show that 18F-FDG image features could perform as strong prognostic and predictive factors of metastasis in osteosarcoma and could provide observations about their inherent biology.

• #19 Prediction of Neoadjuvant Chemotherapy Response in Osteosarcoma Using Convolutional Neural Network of Tumor Center 18F-FDG PET Images

  https://www.mdpi.com/2075-4418/11/11/1976

  The prediction model using the machine learning algorithm has been used to estimate poor outcome for NAC in osteosarcoma, but the 2D CNN prediction model using 18F-FDG PET images before NAC can predict the treatment response prior to chemotherapy in osteosarcoma. Additionally, the performance of a prediction model evaluation was different depending on the intratumor region applied to the 2D CNN network. The 2D CNN prediction model using tumor center 18F-FDG PET images before NAC can be helpful in deciding whether to perform NAC in the treatment of osteosarcoma patients. […] For most of the 20th century, the 5-year survival rate of osteosarcoma was as low as 20%. […] Application of neoadjuvant chemotherapy (NAC) therapy significantly improves long-term survival in patients with high-grade osteosarcoma.

• #20 A Binary Survivability Prediction Classification Model towards Understanding of Osteosarcoma Prognosis | Muthaiyah | Emerging Science Journal

  https://ijournalse.org/index.php/ESJ/article/view/1890

  The objective of this study is to explore effective and innovative machine learning techniques that can assist medical professionals in developing more accurate prognoses that can enhance the survivability of osteosarcoma patients by investigating potential prognostic factors and identifying novel therapeutic approaches. […] The results of this study revealed that both SVM and ANN outperformed random forests in predicting survivability for both the 2-year and 5-year time frames. […] These findings indicate the potential of SVM and ANN as effective tools for predicting osteosarcoma survivability. […] The superior performance of SVM and ANN over random forests highlights the potential of these methods in generating more accurate survivability predictions. […] Further development and refinement of these machine learning techniques hold promise for enhancing their effectiveness and instilling greater confidence among medical professionals and patients in the predictive capabilities of machine learning and artificial intelligence models for osteosarcoma survivability.

• #21 A novel classification predicts prognosis and drug sensitivity in osteosarcoma based on alterations in gene sets | Aging

  https://www.aging-us.com/article/205614/text

  We identified 486 signal pathways that related to prognosis. The four most important signaling pathways (PID IL2 STAT5 PATHWAY, REACTOME INTERLEUKIN 7 SIGNALING, WHITEHURST PACLITAXEL SENSITIVITY, YANG BREAST CANCER ESR1 UP) were screened by 20 machine learning algorithms. […] Each patient with a risk score was divided into a low or high group. There was a significant difference in the survival of two groups. Patients in the low group had favored survival in osteosarcoma. […] The AUC of TARGET was 0.88, 0.79, and 0.77 for 1, 3, and 5 years, respectively, which suggested the model had good predictive value. […] This result suggests a significant difference in the immune status of patients in the high- and low- risk groups, which means that our signature can not only predict the prognosis of patients but also the immune status of osteosarcoma patients, which has the potential value to be applied to predict the immune status of patients. […] This result showed the model identified in the study can predict drug sensitivity.

• #22 Sarcoma – Wikipedia

  https://en.wikipedia.org/wiki/Sarcoma

  The AJCC has identified several factors that affect prognosis of bone sarcomas: […] For soft-tissue sarcomas other than GISTs, factors that affect prognosis include: […] For GISTs, the key factor that affects prognosis is: […] According to data published by the US National Cancer Institute (NCI), the overall 5-year survival for bone sarcomas is 66.9%. […] For soft-tissue sarcomas, the overall 5-year survival (irrespective of stage) is 64.5%, but survival is affected by many factors, including stage.

• #23 Survival Rates for Osteosarcoma | American Cancer Society

  https://www.cancer.org/cancer/types/osteosarcoma/detection-diagnosis-staging/survival-rates.html

  Survival rates can give you an idea of what percentage of people with the same type and stage of cancer are still alive a certain amount of time (usually 5 years) after they were diagnosed. […] Keep in mind that survival rates are estimates and are often based on previous outcomes of large numbers of people who had a specific cancer, but they cant predict what will happen in any particular persons case. […] A relative survival rate compares people with the same type and stage of cancer to people in the overall population. […] The SEER database tracks 5-year relative survival rates for osteosarcoma in the United States, based on how far the cancer has spread. […] These numbers apply only to the stage of the cancer when it is first diagnosed. They do not apply later on if the cancer grows, spreads, or comes back after treatment.

• #24 Survival Rates for Osteosarcoma | American Cancer Society

  https://www.cancer.org/cancer/types/osteosarcoma/detection-diagnosis-staging/survival-rates.html

  People now being diagnosed with osteosarcoma may have a better outlook than these numbers show. Treatments improve over time, and these numbers are based on people who were diagnosed and treated at least 5 years earlier. […] Factors other than the stage of the cancer can also affect survival rates.

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