A prediction model for treatment decisions in high-grade extremity soft-tissue sarcomas: Personalised sarcoma care (PERSARC)

Improving Sarcoma Outcomes: Target Trial Emulation to Compare the Impact of Unplanned and Planned Resections on the Outcome

This study follows the Target Trial Emulation (TTE) framework to assess the impact of unplanned resections (UEs) and planned resections (PEs) of sarcomas on local recurrence-free survival (LRFS), metastasis-free survival (MFS), cancer-specific survival (CSS), and overall survival (OS). Sarcomas, malignant tumors with mesenchymal differentiation, present a significant clinical challenge due to their rarity, complexity, and the frequent occurrence of UEs, which complicates effective management. Our analysis utilized real-world-time data from the Swiss Sarcoma Network, encompassing 429 patients, to compare the impact of UEs and PEs, adjusting for known prognostic factors through a multivariable Cox regression model and propensity score weighting. Our findings reveal a significantly higher risk of local recurrence for UEs and a short-term follow-up period that showed no marked differences in MFS, CSS, and OS between the UE and PE groups, underlining the importance of optimal initial surgical management. Furthermore, tumor grade was validated as a critical prognostic factor, influencing outcomes irrespective of surgical strategy. This study illuminates the need for improved referral systems to specialized sarcoma networks to prevent UEs and advocates for the integration of TTE in sarcoma research to enhance clinical guidelines and decision-making in sarcoma care. Future research should focus on the prospective validations of these findings and the exploration of integrated care models to reduce the incidence of UEs and improve patient outcomes.

Improving Diagnosis and Care for Patients With Sarcoma: Do Real-World General Practitioners Data and Prospective Data Collections Have a Place Next to Clinical Trials?

There has been growing interest in the use of real-world data (RWD) to address clinically and policy-relevant (research) questions that cannot be answered with data from randomized controlled trials (RCTs) alone. This is, for example, the case in rare malignancies such as sarcomas as limited patient numbers pose challenges in conducting RCTs within feasible timeliness, a manageable number of collaborators, and statistical power. This narrative review explores the potential of RWD to generate real-world evidence (RWE) in sarcoma research, elucidating its application across different phases of the patient journey, from prediagnosis to the follow-up/survivorship phase. For instance, examining electronic health records (EHRs) from general practitioners (GPs) enables the exploration of consultation frequency and presenting symptoms in primary care before a sarcoma diagnosis. In addition, alternative study designs that integrate RWD with well-designed observational RCTs may offer relevant information on the effectiveness of clinical treatments. As, especially in cases of ultrarare sarcomas, it can be an extreme challenge to perform well-powered randomized prospective studies. Therefore, it is crucial to support the adaptation of novel study designs. Regarding the follow-up/survivorship phase, examining EHR from primary and secondary care can provide valuable insights into identifying the short- and long-term effects of treatment over an extended follow-up period. The utilization of RWD also comes with several challenges, including issues related to data quality and privacy, as described in this study. Notwithstanding these challenges, this study underscores the potential of RWD to bridge, at least partially, gaps between evidence and practice and holds promise in contributing to the improvement of sarcoma care.

Proteomic features of soft tissue tumours in adolescents and young adults

BACKGROUND

Adolescents and young adult (AYA) patients with soft tissue tumours including sarcomas are an underserved group with disparities in treatment outcomes.

METHODS

To define the molecular features between AYA and older adult (OA) patients, we analysed the proteomic profiles of a large cohort of soft tissue tumours across 10 histological subtypes (AYA n = 66, OA n = 243), and also analysed publicly available functional genomic data from soft tissue tumour cell lines (AYA n = 5, OA n = 8).

RESULTS

Biological hallmarks analysis demonstrates that OA tumours are significantly enriched in MYC targets compared to AYA tumours. By comparing the patient-level proteomic data with functional genomic profiles from sarcoma cell lines, we show that the mRNA splicing pathway is an intrinsic vulnerability in cell lines from OA patients and that components of the spliceosome complex are independent prognostic factors for metastasis free survival in AYA patients.

CONCLUSIONS

Our study highlights the importance of performing age-specific molecular profiling studies to identify risk stratification tools and targeted agents tailored for the clinical management of AYA patients.

UK guidelines for the management of soft tissue sarcomas

Soft tissue sarcomas (STS) are rare tumours arising in mesenchymal tissues and can occur almost anywhere in the body. Their rarity, and the heterogeneity of subtype and location, means that developing evidence-based guidelines is complicated by the limitations of the data available. This makes it more important that STS are managed by expert multidisciplinary teams, to ensure consistent and optimal treatment, recruitment to clinical trials, and the ongoing accumulation of further data and knowledge. The development of appropriate guidance, by an experienced panel referring to the evidence available, is therefore a useful foundation on which to build progress in the field. These guidelines are an update of the previous versions published in 2010 and 2016 [1, 2]. The original guidelines were drawn up by a panel of UK sarcoma specialists convened under the auspices of the British Sarcoma Group (BSG) and were intended to provide a framework for the multidisciplinary care of patients with soft tissue sarcomas. This iteration of the guidance, as well as updating the general multidisciplinary management of soft tissue sarcoma, includes specific sections relating to the management of sarcomas at defined anatomical sites: gynaecological sarcomas, retroperitoneal sarcomas, breast sarcomas, and skin sarcomas. These are generally managed collaboratively by site specific multidisciplinary teams linked to the regional sarcoma specialist team, as stipulated in the recently published sarcoma service specification [3]. In the UK, any patient with a suspected soft tissue sarcoma should be referred to a specialist regional soft tissues sarcoma service, to be managed by a specialist sarcoma multidisciplinary team. Once the diagnosis has been confirmed using appropriate imaging and a tissue biopsy, the main modality of management is usually surgical excision performed by a specialist surgeon, combined with pre- or post-operative radiotherapy for tumours at higher risk for local recurrence. Systemic anti-cancer therapy (SACT) may be utilised in cases where the histological subtype is considered more sensitive to systemic treatment. Regular follow-up is recommended to assess local control, development of metastatic disease, and any late effects of treatment.

Embryonal and alveolar rhabdomyosarcoma in adolescents/young adults, adults and older adults: a population-based cohort study

BACKGROUND

The clinical characteristics, outcomes, and prognostic factors of adult embryonal rhabdomyosarcomas (ERMS) and alveolar rhabdomyosarcomas (ARMS), particularly the differences among adolescents/young adults (AYA), adults, and older adults, remain unclear. We assessed the clinicopathological features and survival outcomes of adult patients with ERMS and ARMS in Japan and to compare these features among AYA, adult, and older adult patients.

METHODS

We retrospectively analyzed data from the Bone and Soft Tissue Tumor Registry of Japan and enrolled patients aged ≥15 years with ERMS and ARMS. Disease-specific overall survival (DOS) was estimated using the Kaplan-Meier method, and a Cox regression model was used to identify prognostic factors.

RESULTS

Among 184 patients with ERMS and ARMS (median age, 27 years; interquartile range, 18-49 years), a high rate of distant and regional nodal metastases was initially observed in 65 (35%) and 66 (36%) cases, respectively. Older age and distant metastasis at first presentation were statistically poor prognostic factors, and histological subtype and site of tumor origin were not associated with DOS. In patients with localized ERMS and ARMS, older age and nodal metastasis were poor prognostic factors; the 5-year DOS rates of patients with and without nodal metastasis were 23% and 72%, respectively.

CONCLUSIONS

Older patients with rhabdomyosarcoma had a dismal prognosis, and distant metastasis was a poor prognostic factor. The prognostic factors differed between adult and pediatric patients with rhabdomyosarcoma; biological analyses, such as genome analysis of adult rhabdomyosarcoma and clinical trials with pediatric oncologists, are needed to improve the prognosis of adult rhabdomyosarcoma.

Unraveling the Myth of Radiation Resistance in Soft Tissue Sarcomas

There is a misconception that sarcomas are resistant to radiotherapy. This manuscript summarizes available (pre-) clinical data on the radiosensitivity of soft tissue sarcomas. Currently, clinical practice guidelines suggest irradiating sarcomas in 1.8-2 Gy once daily fractions. Careful observation of myxoid liposarcomas patients during preoperative radiotherapy led to the discovery of this subtype's remarkable radiosensitivity. It resulted subsequently in an international prospective clinical trial demonstrating the safety of a reduced total dose, yet still delivered with conventional 1.8-2 Gy fractions. In several areas of oncology, especially for tumors of epithelial origin where radiotherapy plays a curative role, the concurrent application of systemic compounds aiming for radiosensitization has been incorporated into routine clinical practice. This approach has also been investigated in sarcomas and is summarized in this manuscript. Observing relatively low α/β ratios after preclinical cellular investigations, investigators have explored hypofractionation with daily doses ranging from 2.85-8.0 Gy per day in prospective clinical studies, and the data are presented. Finally, we summarize work with mouse models and genomic investigations to predict observed responses to radiotherapy in sarcoma patients. Taken together, these data indicate that sarcomas are not resistant to radiation therapy.

Extremity and Truncal Soft Tissue Sarcoma: Risk Assessment and Multidisciplinary Management

Extremity and truncal soft tissue sarcomas are a heterogeneous group of rare cancers that arise from mesenchymal tissues. Hence, the adoption of tailored risk assessment and prognostication tools plays a crucial role in optimizing the decision-making for which of the many possible treatment strategies to select. Management of these tumors requires a multidisciplinary strategy, which has seen significant development in recent decades. Surgery has emerged as the primary treatment approach, with the main goal of achieving microscopic negative tumor margins. To reduce the likelihood of local recurrence, loco-regional treatments such as radiation therapy and isolated limb perfusion are often added to the treatment regimen in combination with surgery. This approach also enables surgeons to perform limb-sparing surgery, particularly in cases where a positive tumor margin is expected. Chemotherapy may also provide a further benefit in decreasing the probability of local recurrence or reducing distant metastasis in selected patients. Selecting the optimal treatment strategy for these rare tumors is best accomplished by an experienced multi-disciplinary team.

Development and external validation of a machine learning model for prediction of survival in extremity leiomyosarcoma

PURPOSE

Machine learning (ML) models have been used to predict cancer survival in several sarcoma subtypes. However, none have investigated extremity leiomyosarcoma (LMS). ML is a powerful tool that has the potential to better prognosticate extremity LMS.

METHODS

The Surveillance, Epidemiology, and End Results (SEER) database was queried for cases of histologic extremity LMS (n = 634). Patient, tumor, and treatment characteristics were recorded, and ML models were developed to predict 1-, 3-, and 5-year survival. The best performing ML model was externally validated using an institutional cohort of extremity LMS patients (n = 46).

RESULTS

All ML models performed best at the 1-year time point and worst at the 5-year time point. On internal validation within the SEER cohort, the best models had c-statistics of 0.75-0.76 at the 5-year time point. The Random Forest (RF) model was the best performing model and used for external validation. This model also performed best at 1-year and worst at 5-year on external validation with c-statistics of 0.90 and 0.87, respectively. The RF model was well calibrated on external validation. This model has been made publicly available at https://rachar.shinyapps.io/lms_app/ CONCLUSIONS: ML models had excellent performance for survival prediction of extremity LMS. Future studies incorporating a larger institutional cohort may be needed to further validate the ML model for LMS prognostication.

The efficacy of re-excision after unplanned excision for synovial sarcoma

Background

This investigation studied the clinical features and outcomes of synovial sarcoma (SS) patients from a single institution.

Methods

A retrospective clinicopathologic study was conducted on 129 postoperative SS patients during 2003-2018. Kaplan-Meier curves and Cox proportional hazards regression (Cox) models were performed to determine the parameters associated with recurrence-free survival (RFS), metastasis-free survival (MFS), and cancer-specific survival (CSS) via univariate and multivariate analysis. The impact of unplanned excision (UE) and residual tumor in re-excision specimens was evaluated.

Results

The 3-year RFS, MFS and 5-year CSS were 72 %, 70 %, and 76 %, respectively. Independent factors associated with significantly inferior survival included older age, UE without re-excision, UE with residual tumors, high grade, and deep tumor for RFS, trunk-related tumor, UE without re-excision, UE with residual tumors, and deep tumor for MFS, UE with residual tumors, high grade, and deep tumor for CSS. Re-excision after UE was significantly associated with better RFS (P < 0.001). Residual tumors were remarkably correlated with inferior RFS (P = 0.0012), MFS (P = 0.0016), and CSS (P = 0.048), especially in patients at stage II (MFS: P < 0.001, CSS: P = 0.0014).

Conclusion

UE and residual tumors have a marked impact on the long-term survival of SS patients. Primary wide excision and re-excision is especially essential for patients at stage II.

Survival after resection of malignant peripheral nerve sheath tumors: Introducing and validating a novel type-specific prognostic model

Background

This study aimed to assess the performance of currently available risk calculators in a cohort of patients with malignant peripheral nerve sheath tumors (MPNST) and to create an MPNST-specific prognostic model including type-specific predictors for overall survival (OS).

Methods

This is a retrospective multicenter cohort study of patients with MPNST from 11 secondary or tertiary centers in The Netherlands, Italy and the United States of America. All patients diagnosed with primary MPNST who underwent macroscopically complete surgical resection from 2000 to 2019 were included in this study. A multivariable Cox proportional hazard model for OS was estimated with prespecified predictors (age, grade, size, NF-1 status, triton status, depth, tumor location, and surgical margin). Model performance was assessed for the Sarculator and PERSARC calculators by examining discrimination (C-index) and calibration (calibration plots and observed-expected statistic; O/E-statistic). Internal-external cross-validation by different regions was performed to evaluate the generalizability of the model.

Results

A total of 507 patients with primary MPNSTs were included from 11 centers in 7 regions. During follow-up (median 8.7 years), 211 patients died. The C-index was 0.60 (95% CI 0.53-0.67) for both Sarculator and PERSARC. The MPNST-specific model had a pooled C-index of 0.69 (95%CI 0.65-0.73) at validation, with adequate discrimination and calibration across regions.

Conclusions

The MPNST-specific MONACO model can be used to predict 3-, 5-, and 10-year OS in patients with primary MPNST who underwent macroscopically complete surgical resection. Further validation may refine the model to inform patients and physicians on prognosis and support them in shared decision-making.

(Cost-)effectiveness of an individualised risk prediction tool (PERSARC) on patient's knowledge and decisional conflict among soft-tissue sarcomas patients: protocol for a parallel cluster randomised trial (the VALUE-PERSARC study)

INTRODUCTION

Current treatment decision-making in high-grade soft-tissue sarcoma (STS) care is not informed by individualised risks for different treatment options and patients' preferences. Risk prediction tools may provide patients and professionals insight in personalised risks and benefits for different treatment options and thereby potentially increase patients' knowledge and reduce decisional conflict. The VALUE-PERSARC study aims to assess the (cost-)effectiveness of a personalised risk assessment tool (PERSARC) to increase patients' knowledge about risks and benefits of treatment options and to reduce decisional conflict in comparison with usual care in high-grade extremity STS patients.

METHODS

The VALUE-PERSARC study is a parallel cluster randomised control trial that aims to include at least 120 primarily diagnosed high-grade extremity STS patients in 6 Dutch hospitals. Eligible patients (≥18 years) are those without a treatment plan and treated with curative intent. Patients with sarcoma subtypes or treatment options not mentioned in PERSARC are unable to participate. Hospitals will be randomised between usual care (control) or care with the use of PERSARC (intervention). In the intervention condition, PERSARC will be used by STS professionals in multidisciplinary tumour boards to guide treatment advice and in patient consultations, where the oncological/orthopaedic surgeon informs the patient about his/her diagnosis and discusses benefits and harms of all relevant treatment options. The primary outcomes are patients' knowledge about risks and benefits of treatment options and decisional conflict (Decisional Conflict Scale) 1 week after the treatment decision has been made. Secondary outcomes will be evaluated using questionnaires, 1 week and 3, 6 and 12 months after the treatment decision. Data will be analysed following an intention-to-treat approach using a linear mixed model and taking into account clustering of patients within hospitals.

ETHICS AND DISSEMINATION

The Medical Ethical Committee Leiden-Den Haag-Delft (METC-LDD) approved this protocol (NL76563.058.21). The results of this study will be reported in a peer-review journal.

TRIAL REGISTRATION NUMBER

NL9160, NCT05741944.

Follow-Up after Curative Surgical Treatment of Soft-Tissue Sarcoma for Early Detection of Recurrence: Which Patients Have More or Fewer Visits than Advised in Guidelines?

INTRODUCTION

Follow-up (FU) in soft-tissue sarcoma (STS) patients is designed for early detection of disease recurrence. Current guidelines are not evidenced-based and not tailored to patient or tumor characteristics, so they remain debated, particularly given concerns about cost, radiation frequency, and over-testing. This study assesses the extent to which STS patients received guideline-concordant FU and to characterize which type of patients received more or fewer visits than advised.

METHODS

All STS patients surgically treated at the Leiden University Medical Center between 2000-2020 were included. For each patient, along with individual characteristics, all radiological examinations from FU start up to 5 years were included and compared to guidelines. Recurrence was defined as local/regional recurrence or metastasis.

RESULTS

A total of 394 patients was included, of whom 250 patients had a high-grade tumor (63.5%). Only 24% of patients received the advised three FU visits in the first year. More FU visits were observed in younger patients and those diagnosed with a high-grade tumor. Among patients with a recurrence, 10% received fewer visits than advised, while 28% of patients without a recurrence received more visits than advised.

CONCLUSIONS

A minority of STS patients received guideline-concordant FU visits, suggesting that clinicians seem to incorporate recurrence risk in decisions on FU frequency.

The proteomic landscape of soft tissue sarcomas

Soft tissue sarcomas (STS) are rare and diverse mesenchymal cancers with limited treatment options. Here we undertake comprehensive proteomic profiling of tumour specimens from 321 STS patients representing 11 histological subtypes. Within leiomyosarcomas, we identify three proteomic subtypes with distinct myogenesis and immune features, anatomical site distribution and survival outcomes. Characterisation of undifferentiated pleomorphic sarcomas and dedifferentiated liposarcomas with low infiltrating CD3 + T-lymphocyte levels nominates the complement cascade as a candidate immunotherapeutic target. Comparative analysis of proteomic and transcriptomic profiles highlights the proteomic-specific features for optimal risk stratification in angiosarcomas. Finally, we define functional signatures termed Sarcoma Proteomic Modules which transcend histological subtype classification and show that a vesicle transport protein signature is an independent prognostic factor for distant metastasis. Our study highlights the utility of proteomics for identifying molecular subgroups with implications for risk stratification and therapy selection and provides a rich resource for future sarcoma research.

Predicting five-year mortality in soft-tissue sarcoma patients

Aims

The aim of this study was to identify factors associated with five-year cancer-related mortality in patients with limb and trunk soft-tissue sarcoma (STS) and develop and validate machine learning algorithms in order to predict five-year cancer-related mortality in these patients.

Methods

Demographic, clinicopathological, and treatment variables of limb and trunk STS patients in the Surveillance, Epidemiology, and End Results Program (SEER) database from 2004 to 2017 were analyzed. Multivariable logistic regression was used to determine factors significantly associated with five-year cancer-related mortality. Various machine learning models were developed and compared using area under the curve (AUC), calibration, and decision curve analysis. The model that performed best on the SEER testing data was further assessed to determine the variables most important in its predictive capacity. This model was externally validated using our institutional dataset.

Results

A total of 13,646 patients with STS from the SEER database were included, of whom 35.9% experienced five-year cancer-related mortality. The random forest model performed the best overall and identified tumour size as the most important variable when predicting mortality in patients with STS, followed by M stage, histological subtype, age, and surgical excision. Each variable was significant in logistic regression. External validation yielded an AUC of 0.752.

Conclusion

This study identified clinically important variables associated with five-year cancer-related mortality in patients with limb and trunk STS, and developed a predictive model that demonstrated good accuracy and predictability. Orthopaedic oncologists may use these findings to further risk-stratify their patients and recommend an optimal course of treatment.

Staging Systems and Nomograms for Soft Tissue Sarcoma

Reliable tools for prognosis prediction are crucially needed by oncologists so they can tailor individual treatments. However, the wide spectrum of histologies and prognostic behaviors of sarcomas challenges their development. In this field, nomograms could definitely better account for their granularity compared to the more widely used AJCC/UICC TNM staging system. Nomograms are predictive tools that incorporate multiple risk factors and return a numerical probability of a clinical event. Since the development of the first nomogram in 2002, several other nomograms have been built, either general, site-specific, histology-specific, or both. Recently, some new “dynamic” nomograms and prognostic tools have been developed, allowing doctors to “recalculate” a patient’s prognosis by taking into account the time since primary surgery, the event history, and the potential time-dependent effect of covariates. Due to these new tools, prognosis prediction is no longer limited to the time of the first computation but can be adapted and recalculated based on the occurrence (or not) of any event as time passes from the first computation. In this review, we aimed to give an overview of the available nomograms for STS and to help clinicians in the process of selecting the best tool for each patient.

Trimodality Treatment of Extremity Soft Tissue Sarcoma: Where Do We Go Now?

OPINION STATEMENT

Extremity soft tissue sarcoma (ESTS) constitutes the majority of patients with soft tissue sarcoma (STS). Patients with localized high-grade ESTS > 5 cm in size carry a substantial risk of developing distant metastasis on follow-up. A neoadjuvant chemoradiotherapy approach can enhance local control by facilitating resection of the large and deep locally advanced tumors while trying to address distant spread by treating the micrometastasis for these high-risk ESTS. Preoperative chemoradiotherapy and adjuvant chemotherapy are often used for children with intermediate- or high-risk non-rhabdomyosarcoma soft tissue tumors in North America and Europe. In adults, the cumulative evidence supporting preoperative chemoradiotherapy or adjuvant chemotherapy remains controversial. However, some studies support a possible benefit of 10% in overall survival (OS) for high-risk localized ESTS, especially for those with a probability of 10-year OS < 60% using validated nomograms. Opponents of neoadjuvant chemotherapy argue that it delays curative surgery, compromises local control, and increases the rate of wound complications and treatment-related mortality; however, the published trials do not support these arguments. Most treatment-related side effects can be managed with adequate supportive care. A coordinated multidisciplinary approach involving sarcoma expertise in surgery, radiation, and chemotherapy is required to achieve better outcomes for ESTS. The next generation of clinical trials will shed light on how comprehensive molecular characterization, targeted agents and/or immunotherapy can be integrated into the upfront trimodality treatment to improve outcomes. To that end, every effort should be made to enroll these patients on clinical trials, when available.

Statistical models versus machine learning for competing risks: development and validation of prognostic models

BACKGROUND

In health research, several chronic diseases are susceptible to competing risks (CRs). Initially, statistical models (SM) were developed to estimate the cumulative incidence of an event in the presence of CRs. As recently there is a growing interest in applying machine learning (ML) for clinical prediction, these techniques have also been extended to model CRs but literature is limited. Here, our aim is to investigate the potential role of ML versus SM for CRs within non-complex data (small/medium sample size, low dimensional setting).

METHODS

A dataset with 3826 retrospectively collected patients with extremity soft-tissue sarcoma (eSTS) and nine predictors is used to evaluate model-predictive performance in terms of discrimination and calibration. Two SM (cause-specific Cox, Fine-Gray) and three ML techniques are compared for CRs in a simple clinical setting. ML models include an original partial logistic artificial neural network for CRs (PLANNCR original), a PLANNCR with novel specifications in terms of architecture (PLANNCR extended), and a random survival forest for CRs (RSFCR). The clinical endpoint is the time in years between surgery and disease progression (event of interest) or death (competing event). Time points of interest are 2, 5, and 10 years.

RESULTS

Based on the original eSTS data, 100 bootstrapped training datasets are drawn. Performance of the final models is assessed on validation data (left out samples) by employing as measures the Brier score and the Area Under the Curve (AUC) with CRs. Miscalibration (absolute accuracy error) is also estimated. Results show that the ML models are able to reach a comparable performance versus the SM at 2, 5, and 10 years regarding both Brier score and AUC (95% confidence intervals overlapped). However, the SM are frequently better calibrated.

CONCLUSIONS

Overall, ML techniques are less practical as they require substantial implementation time (data preprocessing, hyperparameter tuning, computational intensity), whereas regression methods can perform well without the additional workload of model training. As such, for non-complex real life survival data, these techniques should only be applied complementary to SM as exploratory tools of model's performance. More attention to model calibration is urgently needed.

Role of Imaging in Initial Prognostication of Locally Advanced Soft Tissue Sarcomas

BACKGROUND

Although imaging is central in the initial staging of patients with soft tissue sarcomas (STS), it remains underused and few radiological features are currently used in practice for prognostication and to help guide the best therapeutic strategy. Yet, several prognostic qualitative and quantitative characteristics from magnetic resonance imaging (MRI) and positron emission tomography (PET) have been identified over these last decades.

OBJECTIVE

After an overview of the current validated prognostic features based on baseline imaging and their integration into prognostic tools, such as nomograms used by clinicians, the aim of this review is to summarize more complex and innovative MRI, PET, and radiomics features, and to highlight their role to predict indirectly (through histologic grade) or directly the patients' outcomes.

Controversies in the management of patients with soft tissue sarcoma: Recommendations of the Conference on State of Science in Sarcoma 2022

BACKGROUND

Owing to the rarity and heterogeneity in biology and presentation, there are multiple areas in the diagnosis, treatment and follow-up of soft tissue sarcoma (STS), with no, low-level or conflicting evidence.

METHODS

During the first Consensus Conference on the State of Science in Sarcoma (CSSS), we used a modified Delphi process to identify areas of controversy in the field of sarcoma, to name topics with limited evidence-based data in which a scientific and knowledge gap may remain and a consensus statement will help to guide patient management. We determined scientific questions which need to be addressed in the future in order to generate evidence and to inform physicians and caregivers in daily clinical practice in order to improve the outcomes of patients with sarcoma. We conducted a vote on STS key questions and controversies prior to the CSSS meeting, which took place in May 2022.

RESULTS

Sixty-two European sarcoma experts participated in the survey. Sixteen strong consensus (≥95%) items were identified by the experts, as well as 30 items with a ≥75% consensus on diagnostic and therapeutic questions. Ultimately, many controversy topics remained without consensus.

CONCLUSIONS

In this manuscript, we summarise the voting results and the discussion during the CSSS meeting. Future scientific questions, priorities for clinical trials, registries, quality assurance, and action by stakeholders are proposed. Platforms and partnerships can support innovative approaches to improve management and clinical research in STS.

Quality of Sarcoma Care: Longitudinal Real-Time Assessment and Evidence Analytics of Quality Indicators

Sarcomas represent a large group of rare to very rare diseases, requiring complex management with a transdisciplinary approach. Overall progress has been hampered because of discipline, institution and network fragmentation, and there is no global data harmonization or quality standards. To report on and improve quality, a common definition of quality indicators (QIs) of sarcoma care as well as the capacity to assess longitudinal real-time data is required. An international advisory board of world-renowned sarcoma experts defined six categories of QIs, totaling more than 80 quality indicators. An interoperable (web-based) digital platform was then created combining the management of the weekly sarcoma board meeting with the sarcoma registry and incorporating patient-reported outcome measures (PROMs) into the routine follow-up care to assess the entire care cycle of the patient. The QIs were then programmed into the digital platform for real-time analysis and visualization. The definition of standardized QIs covering all physician- (diagnostics and therapeutics), patient- (PROMS/PREMS), and cost-based aspects in combination with their real-time assessment over the entire sarcoma care cycle can be realized. Standardized QIs as well as their real-time assessment and data visualization are critical to improving the quality of sarcoma care. By enabling predictive modelling and introducing VBHC, precision health care for a complex disease is on the horizon.

Bone sarcoma follow-up; a nationwide analysis of oncological events after initial treatment

Aim

Follow-up strategies for high-grade bone sarcomas have been optimized to facilitate early detection of local recurrence and distant metastasis. The ideology is that early detection enables early treatment presuming better survival. However, the clinical value for each individual patient remains questionable. This study aims to evaluate oncological events after initial treatment in order to assess current follow-up strategies for high-grade bone sarcomas in the Netherlands.

Patients and Methods

A retrospective cohort study was conducted based on a national registry. All cases were retrieved from the Netherlands Cancer Registry. Our study consisted of 393 patients treated between 2007 and 2011 with complete follow-up data. Baseline characteristics were analysed for all entities. Local recurrence and distant metastasis was analysed along with overall survival for high-grade chondrosarcoma, high-grade osteosarcoma, Ewing sarcoma and chordoma.

Results

Median follow-up was 8,3 years for high-grade chondrosarcoma, 4,9 for high-grade osteosarcoma, 3,8 for Ewing sarcoma and 7,5 for chordoma. Median time to local recurrence and distant metastasis was 1,2 years for high-grade osteosarcoma and 1,5 years for Ewing sarcoma. For high-grade osteosarcoma with localized disease at presentation, 0.09 new distant metastatic events per patient per year were seen after five years of follow-up with 11,1 patients needed to follow-up for any event. Five-year overall survival was 60,0% for high-grade chondrosarcoma, 50,0% for high-grade osteosarcoma, 45,3% for Ewing sarcoma and 71,4% for chordoma.

Conclusions

This nationwide study shows a plateau in local recurrences and distant metastatic events after four years of treatment for patients with high-grade osteosarcoma and Ewing sarcoma. Due to a lack of reliable evidence however, we were not able to provide additional guidance on follow-up intervals and duration. Collaborative research with larger groups is needed in order to provide a solid scientific recommendation for follow-up in the heterogenous patient population with bone sarcoma.

Nomograms predicting local and distant recurrence and disease-specific mortality for R0/R1 soft tissue sarcomas of the extremities

Background

Prognostic models for patients with soft tissue sarcoma (STS) of the extremities have been developed from large multi-institutional datasets with mixed results. We aimed to develop predictive nomograms for sarcoma-specific survival (SSS) and, for the first time, long-term local recurrence (LR) and distant recurrence (DR) in patients with STS of the extremities treated at our institution.

Patients and methods

Data from patients treated at Humanitas Cancer Center from 1997 to 2015 were analyzed. Variable selection was based on the clinical knowledge and multivariable regression splines algorithm. Perioperative treatments were always included in the model. Prognostic models were developed using Cox proportional hazards model, and model estimates were plotted in nomograms predicting SSS at 5 and 10 years and LR and DR at 2, 5, and 10 years. Model performance was estimated internally via bootstrapping, in terms of optimism-corrected discrimination (Harrell C-index) and calibration (calibration plots).

Results

Data on 517 patients were analyzed. At 5 and 10 years, SSS was 68.1% [95% confidence interval (CI), 63.8–72.1] and 55.6% (50.5–60.3), respectively. LR was 79.1% (95% CI, 75.3–82.4), 71.1% (95% CI, 66.7–75.1), and 66.0% (95% CI, 60.7–70.7) at 2, 5, and 10 years, respectively, whereas DR was 65.9% (95% CI, 61.6–69.9), 57.5% (95% CI, 53.0–61.8), and 52.1% (95% CI, 47.1–56.8) at 2, 5, and 10 years, respectively. SSS nomogram included age, gender, margins, tumor size, grading, and histotype. LR and DR nomograms incorporated mostly the same variables, except for age for DR; LR nomogram did not include gender but included anatomic site. The optimism-corrected C-indexes were 0.73 and 0.72 for SSS at 5 and 10 years, respectively; 0.65, 0.64, and 0.64 for LR at 2, 5, and 10 years, respectively; and 0.68 for DR at 2, 5, and 10 years. Predicted probabilities were close to the observed ones for all outcomes.

Conclusions

We developed and validated three nomograms for STS of the extremities predicting the probability of SSS at 5 and 10 years and LR and DR at 2, 5, and 10 years. By accounting for the perioperative treatment, these models allow prediction for future patients who had no perioperative treatment, thus being useful in the clinical decision-making process.

Prediction tools for the personalized management of soft-tissue sarcomas of the extremity

Prediction tools are instruments which are commonly used to estimate the prognosis in oncology and facilitate clinical decision-making in a more personalized manner. Their popularity is shown by the increasing numbers of prediction tools, which have been described in the medical literature. Many of these tools have been shown to be useful in the field of soft-tissue sarcoma of the extremities (eSTS). In this annotation, we aim to provide an overview of the available prediction tools for eSTS, provide an approach for clinicians to evaluate the performance and usefulness of the available tools for their own patients, and discuss their possible applications in the management of patients with an eSTS.Cite this article: Bone Joint J 2022;104-B(9):1011-1016.

The role of neoadjuvant radiochemotherapy in the management of localized high-grade soft tissue sarcoma

BACKGROUND

Standard treatment of soft tissue sarcoma (STS) of the extremities includes limb-sparing surgery combined with pre- or postoperative radiotherapy (RT). The role of perioperative chemotherapy (CTX) remains uncertain. STS patients with high-risk features for local recurrence, distant metastases, and increased mortality may require additional systemic therapy. The objective of this study was to evaluate predictors of outcome regarding local control (LC), overall survival (OS), and freedom from distant metastases (FFDM) in a large single-center cohort of patients suffering from localized high-grade STS (grade 2/3, G2/G3). Special emphasis was put on a subgroup of patients who received combined neoadjuvant radiochemotherapy (RCT).

METHODS

Overall, 115 adult STS patients were included in this retrospective study. The median follow-up was 34 months. Twenty-three patients (20.0%) were treated with neoadjuvant RCT, 92 (80.0%) received other therapies (adjuvant RT alone (n = 58); neoadjuvant CTX + adjuvant RT (n = 17); adjuvant RCT (n = 10), neoadjuvant RT alone (n = 7)). To assess potential prognostic factors on LC, OS, and FFDM, univariate (UVA) and multivariable (MVA) Cox proportional hazards models were applied.

RESULTS

UVA showed significantly better LC rates in the neoadjuvant RCT group (p = 0.025), with trends in MVA (p = 0.057). The 3-year LC rate was 89.7% in the neoadjuvant RCT group vs. 75.6% in the "other therapies" group. UVA also showed significantly better OS rates in the neoadjuvant RCT group (p = 0.049), however, this was not confirmed in MVA (p = 0.205), the 3-year OS rate was 85.8% for patients treated with neoadjuvant RCT compared to 73.5% in the "other therapies" group. UVA showed significantly better FFDM rates in (p = 0.018) and a trend towards better FFDM rates in MVA (p = 0.059). The 3-year FFDM rate was 89.7% for patients treated with neoadjuvant RCT compared to 65.9% in the "other therapies" group. In the subgroup of patients with G3 STS, neoadjuvant RCT was a significant positive predictor of LC and FFDM in MVA (p = 0.047, p = 0.027) but not for OS. Overall grade 3 and 4 toxicities were significantly higher (p = 0.019) in the neoadjuvant RCT group and occurred in 73.9% vs. 38.0% in patients receiving other therapies.

CONCLUSIONS

The results suggest that neoadjuvant RCT might improve LC and FFDM in patients with localized G3 STS while also being associated with increased acute complication rates. Further prospective research is warranted to confirm these findings.

Management of Synovial Sarcoma and Myxoid Liposarcoma

Synovial sarcoma and myxoid liposarcoma are translocation-related sarcomas, with a high risk of developing distant metastasis, which often affect young patients and which are sensitive to chemo and radiotherapy. Surgery is the mainstay of therapy in localized disease. In these entities, perioperative radiotherapy is frequently administered, and chemotherapy is evaluated in patients with high-risk limb/trunk wall tumors in which an advantage in overall survival has been shown in the latest clinical trials. In the advanced setting, new strategies, such as cellular therapy are being developed in these histologic types, with promising, although still preliminary, results.

Virtual Biopsy in Soft Tissue Sarcoma. How Close Are We?

A shift in radiology to a data-driven specialty has been unlocked by synergistic developments in imaging biomarkers (IB) and computational science. This is advancing the capability to deliver “virtual biopsies” within oncology. The ability to non-invasively probe tumour biology both spatially and temporally would fulfil the potential of imaging to inform management of complex tumours; improving diagnostic accuracy, providing new insights into inter- and intra-tumoral heterogeneity and individualised treatment planning and monitoring. Soft tissue sarcomas (STS) are rare tumours of mesenchymal origin with over 150 histological subtypes and notorious heterogeneity. The combination of inter- and intra-tumoural heterogeneity and the rarity of the disease remain major barriers to effective treatments. We provide an overview of the process of successful IB development, the key imaging and computational advancements in STS including quantitative magnetic resonance imaging, radiomics and artificial intelligence, and the studies to date that have explored the potential biological surrogates to imaging metrics. We discuss the promising future directions of IBs in STS and illustrate how the routine clinical implementation of a virtual biopsy has the potential to revolutionise the management of this group of complex cancers and improve clinical outcomes.

Real-world evidence on perioperative chemotherapy in localized soft tissue sarcoma of the extremities and trunk wall; a population-based study

BACKGROUND

Data from the real-world setting on perioperative chemotherapy in high-risk, localized soft tissue sarcoma (STS) is limited. Real-world data (RWD) includes data derived from patients treated outside clinical trials and often captures long-term follow-up not recorded in clinical trials. The aim of this study was to provide population-based, real-world evidence on perioperative chemotherapy in localized STS.

MATERIAL AND METHODS

Adult patients with localized STS in the extremities or trunk wall treated at Oslo University Hospital, Oslo, Norway from 1998 to 2017 were included in the study. Data were extracted from a prospectively maintained database, supplemented by retrospective review of medical records.

RESULTS

The total study cohort included 806 patients, of whom 154 (19%) received perioperative chemotherapy. A regimen with anthracycline and ifosfamide was given in 141 of 154 cases (92%). During long-term follow-up two patients developed secondary malignancies, cardiac toxicity was registered in 11 patients (7%) and renal toxicity in 12 patients (8%). Seventy-one of 154 patients (46%) were treated outside of clinical trials and constituted the RWD cohort. The median age at surgery was slightly lower and there were more synovial sarcomas and fewer myxofibrosarcomas in the RWD cohort. No difference in chemotherapy dose intensity was observed. The estimated 5-year metastasis-free survival (MFS) in all patients receiving perioperative chemotherapy was 58%. In the RWD cohort 5-year MFS was 53% and in the clinical study cohort 61% (HR 1.24; 95% CI 0.77-2.00).

CONCLUSION

Long-term outcome after perioperative chemotherapy was comparable for patients treated in routine clinical practice to those in clinical trials. Secondary malignancy and cardiac toxicity were observed. The risk of serious late side effects should be included in the decision process on perioperative chemotherapy.

Leiomyosarcoma in the extremities and trunk wall: systematic review and meta-analysis of the oncological outcomes

Background

Leiomyosarcomas are aggressive malignancies which can occur on the trunk and extremities whose pathogenesis is poorly understood. We aim to quantify the prognostic impact of various clinical and pathological markers on survival and recurrence of leiomyosarcomas.

Methods

We conducted a systematic review as per PRISMA protocol. Survival, local recurrence, and metastasis were the outcome measures. Data were extracted from the studies for the outcome variables; the resultant odds ratios (OR) and 95% confidence interval (CI) were used for the synthesis of a forest plot.

Results

Our search revealed thirteen studies comprising 1380 patients. Seven of these 13 publications were since 2012. Our analysis showed that tumor size larger than 5 cm adversely affected the outcome with an OR 3.39 (2.26–5.10, p < 0.01). Other factors which reduced the overall survival were positive margins of excision OR 2.12 (1.36–3.32, p < 0.01). A reduced risk of metastasis has strongly associated the use of radiotherapy with OR 10.84 (4.41–26.61, p < 0.01). Only a few studies analyzed the impact of factors on local recurrence.

Conclusions

Size larger than 5 cm and positive margins of excision are associated with poor overall survival. In comparison, the use of adjuvant radiotherapy was associated with a lower metastatic rate. There is a need for methodically high-quality studies with more uniform study design and reporting to evaluate the impact of various risk factors on local recurrence and metastases.

Level of evidence

Level 1 Prognostic

Sarculator is a Good Model to Predict Survival in Resected Extremity and Trunk Sarcomas in US Patients

BACKGROUND

Sarculator is an online validated nomogram that predicts overall survival of patients with resected, primary extremity sarcomas. However, its ability to accurately predict outcomes in US patients with sarcoma is unknown.

PATIENTS AND METHODS

Patients from the National Cancer Data Base (NCDB) (2006-2016) with resected stage I-III primary extremity or trunk sarcoma were included. Predicted overall survival (pOS) was calculated using the Sarculator algorithm, which includes patient age, tumor size (cm), grade (1-3), and histology, and compared with actual overall survival (aOS). Harrell's C-index was calculated to determine the discriminatory ability of Sarculator (0.7 = good, 0.8 = strong, 1.0 = perfect model), and calibration plots were created.

RESULTS

In total, 9738 patients were included. Five-year pOS was 73.7% compared with aOS of 68.9%. The C-index for the entire cohort was 0.726. By stage, the C-index was 0.730 for stage I, 0.708 for stage II, and 0.679 for stage III. By histology, C-indices were highest for leiomyosarcoma (0.745), myxofibrosarcoma (0.722), and other histologies (0.721). By sociodemographic variables, Sarculator performed better for patients < 50 years (C-index 0.722), of other/unknown race (C-index 0.781), with private insurance (C-index 0.715), treated at a center other than a community cancer programs (C-index > 0.7), and with no comorbidities (C-index 0.716). Outcomes by zip code educational attainment and income were not markedly different (all C-indices > 0.7).

CONCLUSIONS

Sarculator is overall a good predictor of aOS and useful tool for clinicians to aid in survival prognostication. However, clinicians should be aware of populations for whom Sarculator's predictions may be less accurate. Future work could focus on enhancing the Sarculator algorithm specifically for US patients by including demographic variables.

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.

Risk factors for the development of local recurrence in extremity soft-tissue sarcoma

INTRODUCTION

Local recurrence (LR) is one of the main pitfalls in surgery for extremities soft tissue sarcoma (eSTS). Achieving clear histopathological margins is the most important factor to reduce the risk of LR, but the ability to do so depends on not only surgical technique but also the interplay between tumor biology, anatomical location and surgical approach. The balance between postoperative morbidity and oncological benefits in reducing the risk of LR needs to be considered.

AREAS COVERED

This review will cover which etiological factors for the development of eSTS lead to an increased risk of LR and discuss histological subtypes that have a high risk of LR and which surgical and neoadjuvant therapeutic strategies can minimize the risk of LR.

EXPERT OPINION

The traditional view that surgical radicality always results in low rates of LR, while marginality alone always leads to high rates of relapse, is outdated. In the modern era of surgical oncology, limb salvage and high-level function after resectional surgery are the key surgical goals. The best results are achieved by combining effective neoadjuvant treatments with planned bespoke oncological operations that consider the biological and anatomical factors of each individual sarcoma.

The Influence of Personalised Sarcoma Care (PERSARC) Prediction Modelling on Clinical Decision Making in a Multidisciplinary Setting

Background

With soft-tissue sarcoma of the extremity (ESTS) representing a heterogenous group of tumors, management decisions are often made in multidisciplinary team (MDT) meetings. To optimize outcome, nomograms are more commonly used to guide individualized treatment decision making.

Purpose

To evaluate the influence of Personalised Sarcoma Care (PERSARC) on treatment decisions for patients with high-grade ESTS and the ability of the MDT to accurately predict overall survival (OS) and local recurrence (LR) rates.

Methods

Two consecutive meetings were organised. During the first meeting, 36 cases were presented to the MDT. OS and LR rates without the use of PERSARC were estimated by consensus and preferred treatment was recorded for each case. During the second meeting, OS/LR rates calculated with PERSARC were presented to the MDT. Differences between estimated OS/LR rates and PERSARC OS/LR rates were calculated. Variations in preferred treatment protocols were noted.

Results

The MDT underestimated OS when compared to PERSARC in 48.4% of cases. LR rates were overestimated in 41.9% of cases. With the use of PERSARC, the proposed treatment changed for 24 cases.

Conclusion

PERSARC aids the MDT to optimize individualized predicted OS and LR rates, hereby guiding patient-centered care and shared decision making.

Predictive Value of Preoperative Controlling Nutritional Status Score Combined with Fibrinogen-Albumin Ratio in Postoperative Local Recurrence-Free Survival of Patients with Retroperitoneal Liposarcoma

Background

Previous studies have shown that nutrition and systemic inflammation plays an essential role in the development of soft tissue sarcoma. However, few studies have explored the association of clinicopathologic features and local recurrence with nutritional and inflammatory markers in retroperitoneal liposarcoma (RPLS). This study sought to evaluate the prognostic value of the preoperative nutritional and inflammatory markers for local recurrence-free survival (LRFS) among surgical RPLS patients.

Methods

The study included 111 RPLS patients who underwent surgery between May 2010 and June 2019 at the Peking University Cancer Hospital Sarcoma Center. Time-dependent receiver operating characteristic (time-ROC) curve analysis was conducted to evaluate the ability of markers to predict LRFS. The associations of the CONUT-FAR score with clinicopathological variables and LRFS were evaluated.

Results

In the time-ROC curve analysis, the CONUT-FAR score was superior to other nutritional and inflammatory markers in predicting LRFS. The CONUT-FAR score was the only nutritional and inflammatory marker that independently predicted LRFS in the multivariate analysis, and patients with a high CONUT-FAR score (> 11) showed significantly decreased LRFS. Although the CONUT-FAR score failed to discriminate patients with low grade (G1) (p = 0.327) or undergoing incomplete (R2) resection (p = 0.072), it stratified patients with high grade (G2 and G3) or undergoing complete resection (R0/R1) into subgroups with significantly distinct LRFS (p < 0.001). The CONUT-FAR score also showed good clinical utility among patients with different clinical characteristics.

Conclusion

The preoperative CONUT-FAR score reflects both nutritional and inflammatory factors and is an effective predictor of LRFS for surgical RPLS patients.

Patterns of Perioperative Treatment and Survival of Localized, Resected, Intermediate- or High-Grade Soft Tissue Sarcoma: A 2000-2017 Netherlands Cancer Registry Database Analysis

Background

Standard therapy for localized soft tissue sarcoma (STS) is wide, limb-sparing resection. For intermediate- or high-grade tumors, (neo)adjuvant therapies are frequently added to the treatment plan. In this study, data from a Dutch nationwide database are used to (1) assess whether perioperative management of STS follows ESMO guidelines, (2) characterize prognostic factors for overall survival (OS), and (3) assess the association between perioperative treatment and survival.

Methods

All intermediate- or high-grade, localized STS cases, who have undergone surgery and diagnosed between 2000 and 2017, were identified in the Netherlands Cancer Registry (NCR) database. Variables with demographic, treatment, and survival data were obtained. Survival curves were estimated by Kaplan–Meier's method, and the effect of prognostic factors on OS was assessed in a multivariable Cox regression analysis.

Results

A total of 4957 patients were identified. There were slightly more males (54.7%). Median age at diagnosis was 64 years, and 53.6% of the tumors were located in the extremities. Radiotherapy (RT) was administered to 2481 (50.1%) patients, and 252 (5.1%) patients were treated with perioperative systemic chemotherapy. The total use of perioperative RT did not significantly change in the last 20 years, but the timing followed clinical guidelines: preoperative RT increased significantly (2000–2008: 3.7%, 2009–2017: 22.3%; p < 0.001), whereas the use of postoperative RT diminished (2000–2008: 45.9%, 2009–2017: 26.1%; p < 0.001). The use of perioperative chemotherapy slightly decreased (2000–2008: 5.9%, 2009–2017: 4.4%; p = 0.015). 5-year OS was 59.6% (95% CI: 58.2–61.0). Sex, age, year of diagnosis, tumor location, tumor size, histological grade, depth, histological subtype, surgical margins, and the use of perioperative RT were identified as independent predictors for OS.

Conclusion

Preoperative RT is gradually replacing postoperative RT for localized STS in the Netherlands. The use of perioperative chemotherapy is rare and has slightly decreased in recent years. Identified baseline characteristics and treatment factors predicting OS may aid in future treatment decisions.

Follow-up Strategies for Primary Extremity Soft-tissue Sarcoma in Adults: A Systematic Review of the Published Literature

AIM

Follow-up strategies for primary extremity soft-tissue sarcomas (eSTS) in adults were evaluated in a systematic review of the published literature.

MATERIAL AND METHODS

The published literature was reviewed using PubMed. Of 136,646 studies published between 1985 and 2019, 78 original articles met the inclusion criteria. Articles were selected on the basis of the PRISMA guidelines. The selected articles were then cross-searched to identify further publications. August 1, 2019 was used as the concluding date of publication.

RESULTS

A variety of follow-up schedules have been reported in recently published literature. Two official guidelines have been approved by international societies. The guidelines distinguish between high- and low-grade STS, but mention a wide range of follow-up intervals. Established tools of follow-up include computed tomograph, X-rays of the chest, and magnetic resonance imaging of the primary tumor site in addition to clinical observation and physical examination.

CONCLUSION

Further research will be needed to establish evidence-based guidelines and schedules for follow-up strategies in patients with eSTS.

Is 2 mm a wide margin in high-grade conventional chondrosarcomas of the pelvis?

AIMS

Controversy exists as to what should be considered a safe resection margin to minimize local recurrence in high-grade pelvic chondrosarcomas (CS). The aim of this study is to quantify what is a safe margin of resection for high-grade CS of the pelvis.

METHODS

We retrospectively identified 105 non-metastatic patients with high-grade pelvic CS of bone who underwent surgery (limb salvage/amputations) between 2000 and 2018. There were 82 (78%) male and 23 (22%) female patients with a mean age of 55 years (26 to 84). The majority of the patients underwent limb salvage surgery (n = 82; 78%) compared to 23 (22%) who had amputation. In total, 66 (64%) patients were grade 2 CS compared to 38 (36%) grade 3 CS. All patients were assessed for stage, pelvic anatomical classification, type of resection and reconstruction, margin status, local recurrence, distant recurrence, and overall survival. Surgical margins were stratified into millimetres: < 1 mm; > 1 mm but < 2 mm; and > 2 mm.

RESULTS

The disease--specific survival (DSS) at five years was 69% (95% confidence interval (CI) 56% to 81%) and 51% (95% CI 31% to 70%) for grade 2 and 3 CS, respectively (p = 0.092). The local recurrence-free survival (LRFS) at five years was 59% (95% CI 45% to 72%) for grade 2 CS and 42% (95% CI 21% to 63%) for grade 3 CS (p = 0.318). A margin of more than 2 mm was a significant predictor of increased LRFS (p = 0.001). There was a tendency, but without statistical significance, for a > 2 mm margin to be a predictor of improved DSS. Local recurrence (LR) was a highly significant predictor of DSS, analyzed in a competing risk model (p = 0.001).

CONCLUSION

Obtaining wide margins in the pelvis remains challenging for high-grade pelvic CS. On the basis of our study, we conclude that it is necessary to achieve at least a 2 mm margin for optimal oncological outcomes in patients with high-grade CS of the pelvis. Cite this article: Bone Joint J 2021;103-B(6):1150-1154.

Development and validation of a novel prognostic model for long-term overall survival in liposarcoma patients: a population-based study

Objective

To construct and validate a clinically accurate and histology-specific nomogram to predict overall survival (OS) among liposarcoma (LPS) patients.

Methods

We retrospectively screened eligible patients with LPS diagnosed between 2004 and 2015 from the Surveillance, Epidemiology, and End Results database. We screened independent predictors for the nomogram using univariate and multivariate analyses. We then evaluated the prognostic accuracy of the nomogram by receiver operating characteristic (ROC) curve analysis and Harrell’s concordance index. The prognostic performances of the nomogram and the American Joint Committee on Cancer (AJCC) seventh edition staging system were compared using integrated discrimination improvement (IDI), net reclassification improvement (NRI), and decision curve analyses (DCA).

Results

A novel nomogram was developed using independent prognostic variables, which exhibited excellent predictive performances for 3- and 5-year OS according to ROC curves. The C-index proved that the proposed nomogram had better prognostic accuracy for LPS than the traditional AJCC system, while the NRI, IDI, and DCA of the nomogram indicated better clinical net benefit.

Conclusions

The proposed nomogram can predict 3- and 5-year OS of LPS patients with reliable accuracy and may thus help clinicians to develop appropriate clinical therapies and counseling strategies to prolong the life expectancy of these patients.

Management of Soft Tissue Sarcomas in Extremities: Variation in Treatment Recommendations and Surveillance According to Specialty and Continent

Background

This study aimed to provide an insight into clinical decision-making and surveillance strategy of sarcoma specialists for patients with primary soft tissue sarcoma of the extremities (eSTS). The secondary aim was to quantify the role of patient- and tumor-specific factors in the perioperative management.

Methods

Members of sarcoma societies were sent a Web-based 21-item survey about eSTS management. The survey concerned only primary resectable high-grade eSTS in adults.

Results

The study enrolled 396 respondents. The majority of the surgical specialists thought the evidence for perioperative chemotherapy (CTX) for high-grade eSTS was insufficient. Radiotherapy (RTX) was less frequently offered in Asia than in North America and Europe. The specialties and continents also differed regarding the importance of patient and tumor characteristics influencing RTX and CTX recommendation. For surveillance after initial treatment outpatient visits, chest computed tomography (CT) scans, and magnetic resonance images of the extremity were the methods primarily used. The specialists in North America preferred chest CT scan over chest x-ray, whereas those in Asia and Europe had no clear preference.

Discussion

Specialty and continent are important factors contributing to the variation in clinical practice, treatment recommendations, and surveillance of patients with primary resectable high-grade eSTS.

Gene expression profiles for an immunoscore model in bone and soft tissue sarcoma

Background: Immune infiltration is a prognostic marker to clinical outcomes in various solid tumors. However, reports that focus on bone and soft tissue sarcoma are rare. The study aimed to analyze and identify how immune components influence prognosis and develop a novel prognostic system for sarcomas.

Methods: We retrieved the gene expression data from 3 online databases (GEO, TCGA, and TARGET). The immune fraction was estimated using the CIBERSORT algorithm. After that, we re-clustered samples by K-means and constructed immunoscore by the least absolute shrinkage and selection operator (LASSO) Cox regression model. Next, to confirm the prognostic value, nomograms were constructed.

Results: 334 samples diagnosed with 8 tumor types (including osteosarcoma) were involved in our analysis. Patients were next re-clustered into three subgroups (OS, SAR1, and SAR2) through immune composition. Survival analysis showed a significant difference between the two soft tissue groups: patients with a higher proportion of CD8+ T cells, macrophages M1, and mast cells had favorable outcomes (p=0.0018). Immunoscore models were successfully established in OS and SAR2 groups consisting of 12 and 9 cell fractions, respectively. We found immunosocre was an independent factor for overall survival time. Patients with higher immunoscore had poor prognosis (p<0.0001). Patients with metastatic lesions scored higher than those counterparts with localized tumors (p<0.05).

Conclusions: Immune fractions could be a useful tool for the classification and prognosis of bone and soft tissue sarcoma patients. This proposed immunoscore showed a promising impact on survival prediction.

Influence of tumor-infiltrating immune cells on local control rate, distant metastasis, and survival in patients with soft tissue sarcoma

Soft tissue sarcomas (STS) are considered non-immunogenic, although distinct entities respond to anti-tumor agents targeting the tumor microenvironment. This study’s aims were to investigate relationships between tumor-infiltrating immune cells and patient/tumor-related factors, and assess their prognostic value for local recurrence (LR), distant metastasis (DM), and overall survival (OS).

One-hundred-eighty-eight STS-patients (87 females [46.3%]; median age: 62.5 years) were retrospectively analyzed. Tissue microarrays (in total 1266 cores) were stained with multiplex immunohistochemistry and analyzed with multispectral imaging. Seven cell types were differentiated depending on marker profiles (CD3+, CD3+ CD4+ helper, CD3+ CD8+ cytotoxic, CD3+ CD4+ CD45RO+ helper memory, CD3+ CD8+ CD45RO+ cytotoxic memory T-cells; CD20 + B-cells; CD68+ macrophages). Correlations between phenotype abundance and variables were analyzed. Uni- and multivariate Fine&Gray and Cox-regression models were constructed to investigate prognostic variables. Model calibration was assessed with C-index. IHC-findings were validated with TCGA-SARC gene expression data of genes specific for macrophages, T- and B-cells.

B-cell percentage was lower in patients older than 62.5 years (p = .013), whilst macrophage percentage was higher (p = .002). High B-cell (p = .035) and macrophage levels (p = .003) were associated with increased LR-risk in the univariate analysis. In the multivariate setting, high macrophage levels (p = .014) were associated with increased LR-risk, irrespective of margins, age, gender or B-cells. Other immune cells were not associated with outcome events.

High macrophage levels were a poor prognostic factor for LR, irrespective of margins, B-cells, gender and age. Thus, anti-tumor, macrophage-targeting agents may be applied more frequently in tumors with enhanced macrophage infiltration.

Should metastatic lymph nodes be considered at the same clinical stage as distant metastasis in soft tissue sarcomas?

INTRODUCTION

Lymph node metastasis (LNM) in soft tissue sarcomas (STS) are uncommon, occurring in only 3% - 5% of all sarcomas, and are classified as Stage IV, along with distant metastasis (DM). This paper compares the prognosis of patients with lymphatic and DM, in extremity STS (eSTS).

METHODS

A retrospective study was carried out in a high-volume sarcoma center; 853 patients with eSTS sarcomas were identified and classified from January 1, 1997 to December 31, 2017. Cases with pathological confirmation of LNM were included. Five-year survival rates were analyzed using the Kaplan-Meier method and the Cox proportional hazards model.

RESULTS

LNM was present in 46 of the cases (5.4%), with an overall survival of 21 months (95% confidence interval [CI], 16.7 - 25.2), compared to 18 months (95% confidence interval [CI], 14.2 - 21.7) in those with only DM. Median recurrence-free survival was 21 months (95% confidence interval [CI], 19.7 - 22.4), vs. 20 months (95% confidence interval [CI], 16.2- 23.7), respectively. LNM only and DM only had also a similar OS of 21 months (95% CI 16.7-25.2) vs 18 months (95% CI 14.2-21.7. N1M1 cases had the worse median OS with 15 months (95% confidence interval [CI], 10.9-19.7) CONCLUSIONS: Overall survival and recurrence free survival in patients with lymph node disease and metastatic disease are similar. However prognosis is worse in N1M1. Use of systemic treatment in patients with LNM is not as common as in metastatic cases, this difference in treatment and the fact that prognosis is similar suggests that both biological behavior and effect of treatment have been underestimated. A subclassification of clinical stage IV might be the next step.

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.

Dynamic prediction of overall survival: a retrospective analysis on 979 patients with Ewing sarcoma from the German registry

OBJECTIVES

This study aimed at developing a dynamic prediction model for patients with Ewing sarcoma (ES) to provide predictions at different follow-up times. During follow-up, disease-related information becomes available, which has an impact on a patient's prognosis. Many prediction models include predictors available at baseline and do not consider the evolution of disease over time.

SETTING

In the analysis, 979 patients with ES from the Gesellschaft für Pädiatrische Onkologie und Hämatologie registry, who underwent surgery and treatment between 1999 and 2009, were included.

DESIGN

A dynamic prediction model was developed to predict updated 5-year survival probabilities from different prediction time points during follow-up. Time-dependent variables, such as local recurrence (LR) and distant metastasis (DM), as well as covariates measured at baseline, were included in the model. The time effects of covariates were investigated by using interaction terms between each variable and time.

RESULTS

Developing LR, DM in the lungs (DMp) or extrapulmonary DM (DMo) has a strong effect on the probability of surviving an additional 5 years with HRs and 95% CIs equal to 20.881 (14.365 to 30.353), 6.759 (4.465 to 10.230) and 17.532 (13.210 to 23.268), respectively. The effects of primary tumour location, postoperative radiotherapy (PORT), histological response and disease extent at diagnosis on survival were found to change over time. The HR of PORT versus no PORT at the time of surgery is equal to 0.774 (0.594 to 1.008). One year after surgery, the HR is equal to 1.091 (0.851 to 1.397).

CONCLUSIONS

The time-varying effects of several baseline variables, as well as the strong impact of time-dependent variables, show the importance of including updated information collected during follow-up in the prediction model to provide accurate predictions of survival.

Strategies for care of patients with gastrointestinal stromal tumor or soft tissue sarcoma during COVID-19 pandemic: A guide for surgical oncologists

The coronavirus disease-2019 (COVID-19) pandemic is deeply impacting the accessibility of cancer patients to surgery. In resource-limited conditions, the standard of care might not be deliverable, but evidence to support alternative management strategies often exists. By revisiting available treatment options, this review provides surgical oncologists with an evidence-based framework for treating patients with gastrointestinal stromal tumor, extremity/truncal soft tissue sarcoma, and retroperitoneal sarcoma to rapidly adapt their decision-making to the constant evolution of the COVID-19 pandemic.

Follow-Up in Bone Sarcoma Care: A Cross-Sectional European Study

Background

Follow-up of high-grade bone sarcoma patients with repeated radiological imaging aims at early detection of recurrent disease or distant metastasis. Repeated radiological imaging does expose (mostly young) patients to ionising radiation. At this point, it is not known whether frequent follow-up increases overall survival. Additionally, frequent follow-up subjects patients and families to psychological stress. This study aims to assess follow-up procedures in terms of frequency and type of imaging modalities in bone tumour centres across Europe for comparison and improvement of knowledge as a first step towards a more uniform approach towards bone sarcoma follow-up.

Methods

Data were obtained through analysis of several follow-up protocols and a digital questionnaire returned by EMSOS members of bone tumour centres all across Europe.

Results

All participating bone tumour centres attained a minimum follow-up period of ten years. National guidelines revealed variations in follow-up intervals and use of repeated imaging with ionising radiation. A local and a chest X-ray were obtained at 47.6% of the responding clinics at every follow-up patient visit.

Conclusions

Variations were seen among European bone sarcoma centres with regards to follow-up intervals and use of repeated imaging. The majority of these expert centres follow existing international guidelines and find them sufficient as basis for a follow-up surveillance programme despite lack of evidence. Future research should aim towards evidence-based follow-up with focus on the effects of follow-up strategies on health outcomes, cost-effectiveness, and individualised follow-up algorithms.

Clinical and Radiologic Features Together Better Predict Lung Nodule Malignancy in Patients with Soft-Tissue Sarcoma

We test the hypothesis that a model including clinical and computed tomography (CT) features may allow discrimination between benign and malignant lung nodules in patients with soft-tissue sarcoma (STS). Seventy-one patients with STS undergoing their first lung metastasectomy were examined. The performance of multiple logistic regression models including CT features alone, clinical features alone, and combined features, was tested to evaluate the best model in discriminating malignant from benign nodules. The likelihood of malignancy increased by more than 11, 2, 6 and 7 fold, respectively, when histological synovial sarcoma sub-type was associated with the following CT nodule features: size ≥ 5.6 mm, well defined margins, increased size from baseline CT, and new onset at preoperative CT. Likewise, in the case of grade III primary tumor, the odds ratio (OR) increased by more than 17 times when the diameter of pulmonary nodules (PNs) was >5.6 mm, more than 13 times with well-defined margins, more than 7 times with PNs increased from baseline CT, and more than 20 times when there were new-onset nodules. Finally, when CT nodule was ≥5.6 in size, it had well-defined margins, it increased in size from baseline CT, and when new onset nodules at preoperative CT were concomitant to residual primary tumor R2, the risk of malignancy increased by more than 10, 6, 25 and 28 times, respectively. The combination of clinical and CT features has the highest predictive value for detecting the malignancy of pulmonary nodules in patients with soft tissue sarcoma, allowing early detection of nodule malignancy and treatment options.

Designing a Rational Follow-Up Schedule for Patients with Extremity Soft Tissue Sarcoma

PURPOSE

The risk of tumor recurrence after resection of soft tissue sarcoma (STS) necessitates surveillance in follow-up. The objective of this study was to determine the frequency/timing of metastasis and local recurrence following treatment for soft tissue sarcoma, and to use these data to justify an evidence-based follow-up schedule.

METHODS

Utilizing a prospective database, a retrospective single center review was performed of all patients with minimum 2-year follow-up after resection of a localized extremity STS. Kaplan-Meier estimates were used to calculate the incidence of local recurrence and metastases on an annual basis for 10 years.

RESULTS

We identified a total of 230 low-grade, 626 intermediate-grade and 940 high-grade extremity STS and a total of 721 events, 150 local recurrences and 571 metastases. Based on tumor size and grade, follow-up cohorts were developed that had similar metastatic risk. Using pre-determined thresholds for metastatic event, a follow-up schedule was established for each cohort.

CONCLUSION

Based on our results we recommend that patients with small low-grade tumors undergo annual follow-up for 5 years following definitive local treatment. Patients with large low-grade tumors, small intermediate-grade and small high-grade tumors should have follow-up every 6 months for the first 2 years, then yearly to 10 years. Only patients with large intermediate- or high-grade tumors require follow-up every 3 months for the first 2 years, then every 6 months for years 3-5, followed by annually until 10 years.

Oncological Treatment Considerations Differ across Surgical Subspecialties Treating Malignant Peripheral Nerve Sheath Tumors: An International Survey

Background

Malignant peripheral nerve sheath tumors (MPNSTs) are rare and aggressive soft tissue sarcomas (STS) that, because of their origin, are operated by several surgical subspecialties. This may cause differences in oncologic treatment recommendations based on presentation. This study investigated these differences both within and between subspecialties.

Methods

A survey was distributed among several (inter)national surgical societies. Differences within and between subspecialties were analyzed by χ²-tests.

Results

In total, 30 surgical oncologists, 30 neurosurgeons, 85 plastic surgeons, and 29 “others” filled out the survey. Annual caseload, tumor sites operated, and fellowship training differed significantly between subspecialties. While most surgeons agreed upon preoperative use of MRI, the use of radiological staging and FDG-PET use differed between subspecialties. Surgical oncologists agreed upon core needle biopsies as an ideal type of biopsy while other subspecialties differed in opinion. On average, 53% of surgeons always consider preservation of function preoperatively, but 42% would never perform less extensive resections for function preservation. Respondents agreed that radiotherapy should be considered in tumor sizes >10 cm, microscopic, and macroscopic positive margins. A preferred sequence of radiotherapy administration differed between subspecialties. There was no consensus on indications and sequence of administration of chemotherapy in localized disease.

Conclusion

Surgical oncologists generally agree on preoperative diagnostics; other subspecialties do not. Considering the preservation of function differed among all subspecialties. Surgeons do agree on some indications for radiotherapy, yet the use of chemotherapy in localized MPNSTs lacks consensus. A preferred sequence of multimodal therapy differs between and within surgical subspecialties, but surgical oncologists prefer neoadjuvant radiotherapy.