External validation and adaptation of a dynamic prediction model for patients with high‐grade extremity soft tissue sarcoma

Background and Objectives: A dynamic prediction model for patients with soft tissue sarcoma of the extremities was previously developed to predict updated overall survival probabilities throughout patient follow‐up. This study updates and externally validates the dynamic model. Methods: Data from 3826 patients with high‐grade extremity soft tissue sarcoma, treated surgically with curative intent were used to update the dynamic PERsonalised SARcoma Care (PERSARC) model. Patients were added to the model development cohort and grade was included in the model. External validation was performed with data from 1111 patients treated at a single tertiary center. Results: Calibration plots show good model calibration. Dynamic C‐indices suggest that the model can discriminate between high‐ and low‐risk patients. The dynamic C‐indices at 0, 1, 2, 3, 4, and 5 years after surgery were equal to 0.697, 0.790, 0.822, 0.818, 0.812, and 0.827, respectively. Conclusion: Results from the external validation show that the dynamic PERSARC model is reliable in predicting the probability of surviving an additional 5 years from a specific prediction time point during follow‐up. The model combines patient‐, treatment‐specific and time‐dependent variables such as local recurrence and distant metastasis to provide accurate survival predictions throughout follow‐up and is available through the PERSARC app.Peer reviewe

Age-related differences of oncological outcomes in primary extremity soft tissue sarcoma: a multistate model including 6260 patients

Purpose: No studies extensively compared the young adults (YA, 18-39 years), middle-aged (40-69 years), and elderly (≥70 years) population with primary high-grade extremity soft tissue sarcoma (eSTS). This study aimed to determine whether the known effect of age on overall survival (OS) and disease progression can be explained by differences in tumour characteristics and treatment protocol among the YA, middle-aged and elderly population in patients with primary high-grade eSTS treated with curative intent. Methods: In this retrospective multicentre study, inclusion criteria were patients with primary high-grade eSTS of 18 years and older, surgically treated with curative intent between 2000 and 2016. Cox proportional hazard models and a multistate model were used to determine the association of age on OS and disease progression. Results: A total of 6260 patients were included in this study. YA presented more often after 'whoops'-surgery or for reresection due to residual disease, and with more deep-seated tumours. Elderly patients presented more often with grade III and larger (≥10 cm) tumours. After adjustment for the imbalance in tumour and treatment characteristics the hazard ratio for OS of the middle-aged population is 1.47 (95% confidence interval [CI]: 1.23-1.76) and 3.13 (95% CI: 2.59-3.78) in the elderly population, compared with YA. Discussion: The effect of age on OS could only partially be explained by the imbalance in the tumour characteristics and treatment variables. The threefold higher risk of elderly could, at least partially, be explained by a higher other-cause mortality. The results might also be explained by a different tumour behaviour or suboptimal treatment in elderly compared with the younger population. Keywords: Adolescents and young adults; Elderly; Extremities; Metastasis; Middle-aged; Recurrence; Soft tissue sarcoma; Survival.Peer reviewe

External validation and adaptation of a dynamic prediction model for patients with high-grade extremity soft tissue sarcoma

Background and Objectives: A dynamic prediction model for patients with soft tissue sarcoma of the extremities was previously developed to predict updated overall survival probabilities throughout patient follow-up. This study updates and externally validates the dynamic model. Methods: Data from 3826 patients with high-grade extremity soft tissue sarcoma, treated surgically with curative intent were used to update the dynamic PERsonalised SARcoma Care (PERSARC) model. Patients were added to the model development cohort and grade was included in the model. External validation was performed with data from 1111 patients treated at a single tertiary center. Results: Calibration plots show good model calibration. Dynamic C-indices suggest that the model can discriminate between high- and low-risk patients. The dynamic C-indices at 0, 1, 2, 3, 4, and 5 years after surgery were equal to 0.697, 0.790, 0.822, 0.818, 0.812, and 0.827, respectively. Conclusion: Results from the external validation show that the dynamic PERSARC model is reliable in predicting the probability of surviving an additional 5 years from a specific prediction time point during follow-up. The model combines patient-, treatment-specific and time-dependent variables such as local recurrence and distant metastasis to provide accurate survival predictions throughout follow-up and is available through the PERSARC app

The role of perioperative chemotherapy in primary high-grade extremity soft tissue sarcoma: a risk-stratified analysis using PERSARC

OBJECTIVE: The aim of the study is to assess the effect of perioperative chemotherapy (CTX) in patients with grade II-III extremity soft tissue sarcoma (eSTS) on overall survival (OS) and evaluate whether the PERSARC prediction tool could identify patients with eSTS more likely to benefit from CTX. METHODS: Patients (18-70 years) with primary high-grade eSTS surgically treated with curative intent were included in the retrospective cohort study. The effect of any perioperative CTX and anthracycline + ifosfamide (AI)-based CTX on OS was investigated in three PERSARC-risk groups (high/intermediate/low). The PERSARC-risk groups were defined by the 33% and 66% quantile of the predicted 5-year OS of the study population equal to a 5-year OS of 65.8% and 79.8%, respectively. The effect of CTX on OS was investigated with weighted Kaplan-Meier curves and multivariable Cox models with an interaction between risk group and CTX. RESULTS: This study included 5683 patients. The weighted Kaplan-Meier curves did not demonstrate a beneficial effect of any CTX and AI-based CTX on OS in the overall population. However, in the high PERSARC-risk group the 5-year OS of AI-based CTX was significantly better than no CTX (69.8% vs 59.0%, respectively, p = 0.004) (HR 0.66, 95%CI 0.53-0.83). CONCLUSIONS: This study demonstrated a beneficial effect of AI-based CTX on OS in a selected group of high-risk patients with an absolute survival benefit of 11% as stratified by the PERSARC prediction tool. However, no beneficial effect of CTX on OS was found in the overall population of patients with primary high-grade eSTS younger than 70 years

Machine learning–based biomarker profile derived from 4210 serially measured proteins predicts clinical outcome of patients with heart failure

Aims Risk assessment tools are needed for timely identification of patients with heart failure (HF) with reduced ejection fraction (HFrEF) who are at high risk of adverse events. In this study, we aim to derive a small set out of 4210 repeatedly measured proteins, which, along with clinical characteristics and established biomarkers, carry optimal prognostic capacity for adverse events, in patients with HFrEF. Methods and results In 382 patients, we performed repeated blood sampling (median follow-up: 2.1 years) and applied an aptamer-based multiplex proteomic approach. We used machine learning to select the optimal set of predictors for the primary endpoint (PEP: composite of cardiovascular death, heart transplantation, left ventricular assist device implantation, and HF hospitalization). The association between repeated measures of selected proteins and PEP was investigated by multivariable joint models. Internal validation (cross-validated c-index) and external validation (Henry Ford HF PharmacoGenomic Registry cohort) were performed. Nine proteins were selected in addition to the MAGGIC risk score, N-terminal pro-hormone B-type natriuretic peptide, and troponin T: suppression of tumourigenicity 2, tryptophanyl-tRNA synthetase cytoplasmic, histone H2A Type 3, angiotensinogen, deltex-1, thrombospondin-4, ADAMTS-like protein 2, anthrax toxin receptor 1, and cathepsin D. N-terminal pro-hormone B-type natriuretic peptide and angiotensinogen showed the strongest associations [hazard ratio (95% confidence interval): 1.96 (1.17–3.40) and 0.66 (0.49–0.88), respectively]. The multivariable model yielded a c-index of 0.85 upon internal validation and c-indices up to 0.80 upon external validation. The c-index was higher than that of a model containing established risk factors (P = 0.021). Conclusion Nine serially measured proteins captured the most essential prognostic information for the occurrence of adverse events in patients with HFrEF, and provided incremental value for HF prognostication beyond established risk factors. These proteins could be used for dynamic, individual risk assessment in a prospective setting. These findings also illustrate the potential value of relatively ‘novel’ biomarkers for prognostication.</p

Surgical outcomes of patients with diffuse-type tenosynovial giant-cell tumours: an international, retrospective, cohort study

BACKGROUND: Diffuse-type tenosynovial giant-cell tumour is a rare, locally aggressive, and difficult-to-treat soft tissue tumour. Clinical and surgical outcomes depend on multiple factors, including preoperative diagnostic assessment, the localisation and extent of disease, and possibly the choice of treatment modalities by orthopaedic surgeons. We did a retrospective cohort study to characterise global surgical treatment protocols, and assess surgical outcomes, complications, and functional results in patients with diffuse-type tenosynovial giant-cell tumours. METHODS: In this international, multicentre, retrospective cohort study, we included consecutive patients treated in 31 sarcoma reference centres between Jan 1, 1990, and Dec 31, 2017. Eligible patients were of any age and had histologically proven diffuse-type tenosynovial giant-cell tumour of large joints. Patient data were retrieved from the local databases of participating centres. Patients with localised-type tenosynovial giant-cell tumour were excluded. In the analysis, we only included patients with complete core criteria data regarding admission status, date of treatment, type of treatment at participating centre, and first local recurrence after treatment. We used a non-parametric method to estimate recurrence-free survival at 3, 5, and 10 years after initial surgical resection in a tertiary centre. We used a multivariate Cox regression model to estimate the effect of risk factors. We also present subgroup analyses of disease status at presentation (primary vs recurrent disease) and recurrence-free survival by surgery type (open surgery vs arthroscopic synovectomy), and prespecified risk factors were tested in a univariate and multivariable analyses, with an endpoint of first local recurrence after treatment in a tertiary centre. FINDINGS: Data collection for these analyses occurred between January, 2016, and May, 2018. We received the records of 1192 patients, of which 966 (81%) were surgically treated and had complete information on core criteria. 445 patients were admitted with therapy-naive disease of the knee and were primarily treated in a tertiary centre. Since patients with wait and see treatment do not have a starting date of treatment, these patients were excluded in the calculation of median follow-up time for all patients. For this calculation we used time of surgery as a starting date. 758 (64%) of 1192 patients had knee involvement and 628 (54%) of 1163 patients with complete data on type of surgery had one-staged open synovectomy. At a median follow-up of 54 months (IQR 27-97), recurrent disease developed in 425 (44%) of all 966 surgically treated cases, and recurrence-free survival was 62% (95% CI 59-65) at 3 years, 55% (51-58) at 5 years, and 40% (35-45) at 10 years. Surgical complications were reported in 105 (12%) of 906 patients who had complete data on surgical complications. Pain improved after surgical treatment in 255 (59%) of 434 patients and swelling improved in 328 (72%) of 453 patients who had complete data. INTERPRETATION: This study of patients with diffuse-type tenosynovial giant-cell tumour provides a comprehensive and up-to-date disease overview, assessing the clinical profile and management of the disease in multiple specialised referral centres. Surgical treatment of diffuse-type tenosynovial giant cell tumours is not a definitive treatment for every patient because it involves a high risk for local recurrent disease and a relatively high risk for postoperative complications. After surgical treatment in treatment-naive patients, risk factors for recurrent disease in individual patients were not identified in what we believe is the largest cohort to date. FUNDING: Daiichi Sankyo

Dynamic Digital Twin: Diagnosis, Treatment, Prediction, and Prevention of Disease During the Life Course

A digital twin (DT), originally defined as a virtual representation of a physical asset, system, or process, is a new concept in health care. A DT in health care is not a single technology but a domain-adapted multimodal modeling approach incorporating the acquisition, management, analysis, prediction, and interpretation of data, aiming to improve medical decision-making. However, there are many challenges and barriers that must be overcome before a DT can be used in health care. In this viewpoint paper, we build on the current literature, address these challenges, and describe a dynamic DT in health care for optimizing individual patient health care journeys, specifically for women at risk for cardiovascular complications in the preconception and pregnancy periods and across the life course. We describe how we can commit multiple domains to developing this DT. With our cross-domain definition of the DT, we aim to define future goals, trade-offs, and methods that will guide the development of the dynamic DT and implementation strategies in health care

Surgical outcomes of patients with diffuse-type tenosynovial giant-cell tumours: an international, retrospective, cohort study

BACKGROUND: Diffuse-type tenosynovial giant-cell tumour is a rare, locally aggressive, and difficult-to-treat soft tissue tumour. Clinical and surgical outcomes depend on multiple factors, including preoperative diagnostic assessment, the localisation and extent of disease, and possibly the choice of treatment modalities by orthopaedic surgeons. We did a retrospective cohort study to characterise global surgical treatment protocols, and assess surgical outcomes, complications, and functional results in patients with diffuse-type tenosynovial giant-cell tumours. METHODS: In this international, multicentre, retrospective cohort study, we included consecutive patients treated in 31 sarcoma reference centres between Jan 1, 1990, and Dec 31, 2017. Eligible patients were of any age and had histologically proven diffuse-type tenosynovial giant-cell tumour of large joints. Patient data were retrieved from the local databases of participating centres. Patients with localised-type tenosynovial giant-cell tumour were excluded. In the analysis, we only included patients with complete core criteria data regarding admission status, date of treatment, type of treatment at participating centre, and first local recurrence after treatment. We used a non-parametric method to estimate recurrence-free survival at 3, 5, and 10 years after initial surgical resection in a tertiary centre. We used a multivariate Cox regression model to estimate the effect of risk factors. We also present subgroup analyses of disease status at presentation (primary vs recurrent disease) and recurrence-free survival by surgery type (open surgery vs arthroscopic synovectomy), and prespecified risk factors were tested in a univariate and multivariable analyses, with an endpoint of first local recurrence after treatment in a tertiary centre. FINDINGS: Data collection for these analyses occurred between January, 2016, and May, 2018. We received the records of 1192 patients, of which 966 (81%) were surgically treated and had complete information on core criteria. 445 patients were admitted with therapy-naive disease of the knee and were primarily treated in a tertiary centre. Since patients with wait and see treatment do not have a starting date of treatment, these patients were excluded in the calculation of median follow-up time for all patients. For this calculation we used time of surgery as a starting date. 758 (64%) of 1192 patients had knee involvement and 628 (54%) of 1163 patients with complete data on type of surgery had one-staged open synovectomy. At a median follow-up of 54 months (IQR 27-97), recurrent disease developed in 425 (44%) of all 966 surgically treated cases, and recurrence-free survival was 62% (95% CI 59-65) at 3 years, 55% (51-58) at 5 years, and 40% (35-45) at 10 years. Surgical complications were reported in 105 (12%) of 906 patients who had complete data on surgical complications. Pain improved after surgical treatment in 255 (59%) of 434 patients and swelling improved in 328 (72%) of 453 patients who had complete data. INTERPRETATION: This study of patients with diffuse-type tenosynovial giant-cell tumour provides a comprehensive and up-to-date disease overview, assessing the clinical profile and management of the disease in multiple specialised referral centres. Surgical treatment of diffuse-type tenosynovial giant cell tumours is not a definitive treatment for every patient because it involves a high risk for local recurrent disease and a relatively high risk for postoperative complications. After surgical treatment in treatment-naive patients, risk factors for recurrent disease in individual patients were not identified in what we believe is the largest cohort to date. FUNDING: Daiichi Sankyo