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Background: Missing covariates are common in observational research and can lead to bias and loss of statistical power. Limited data regarding prognostic factors of survival outcomes of sarcomas in irradiated fields (SIF) are available. Because of the long lag time between irradiation of first cancer and scarcity of SIF, missing data are a critical issue when analyzing long-term outcomes. We assessed prognostic factors of overall (OS), progression-free (PFS), and metastatic-progression-free (MPFS) survivals in SIF using three methods to account for missing covariates. Methods: We relied on the NETSARC French Sarcoma Group database, Cox (OS/PFS), and competitive hazards (MPFS) survival models. Covariates investigated were age, sex, histological subtype, tumor size, depth and grade, metastasis, surgery, surgical resection, surgeon's expertise, imaging, and neo-adjuvant treatment. We first applied multiple imputation (MI): observed data were used to estimate the missing covariate. With the missing-data modality approach, a category missing was created for qualitative variables. With the complete-case (CC) approach, analysis was restricted to patients without missing covariates. Results: CC subjects (N = 167; 33%) presented more often with soft-tissue sarcoma (versus visceral sarcoma) and grade I-II tumors as compared to the 504 eligible cases. With MI (N = 504), factors associated with the worst outcome included metastasis (p = 0.04) and R1/R2 resection (p < 0.001) for OS; higher grade/non-gradable tumors (p = 0.002) and R1/R2 resection (p < 0.001) for PFS; and metastasis (p = 0.01) for M-PFS. The 'missing-data modality' approach (N = 504) led to different associations, including significance reached due to variables with the modality 'missing'. The CC analysis led to different results and reduced precision. Conclusion: The CC population was not representative of the eligible population, introducing bias, in addition to worst precision. The 'missing-data modality method' results in biased estimates in non-randomized studies, as outcomes may be related to variables with missing values. Appropriate statistical methods for missing covariates, for example, MI, should therefore be considered.
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OBJECTIVE: This study examined the types of discordance occurring in the diagnosis of soft tissue and visceral sarcomas, gastrointestinal stromal tumors (GIST), and desmoid tumors, as well as the economic impact of diagnostic discrepancies. METHODS: We carried out a retrospective, multicenter analysis using prospectively implemented databases performed on a cohort of patients within the French RRePS network in 2010. Diagnoses were deemed to be discordant based on the 2013 World Health Organization (WHO) classification. Predictive factors of discordant diagnoses were explored. A decision tree was used to assess the expected costs of two strategies of disease management: one based on revised diagnoses after centralized histological review (option 1), the other on diagnoses without centralized review (option 2). Both were defined based on the patient and the disease characteristics, according to national or international guidelines. The time horizon was 12 months and the perspective of the French National Health Insurance (NHI) was retained. Costs were expressed in Euros for 2013. Sensitivity analyses were performed using low and high scenarios that included ± 20% estimates for cost. RESULTS: A total of 2,425 patients were included. Three hundred forty-one patients (14%) had received discordant diagnoses. These discordances were determined to mainly be benign tumors diagnosed as sarcomas (n = 124), or non-sarcoma malignant tumors diagnosed as sarcomas (n = 77). The probability of discordance was higher for a final diagnosis of desmoid tumors when compared to liposarcomas (odds ratio = 5.1; 95%CI [2.6-10.4]). The expected costs per patient for the base-case analysis (low- and high-case scenarios) amounted to 8,791 (7,033 and 10,549, respectively) for option 1 and 8,904 (7,057 and 10,750, respectively) for option 2. CONCLUSIONS: Our findings highlight misdiagnoses of sarcomas, which were found to most often be confused with benign tumors. Centralized histological reviews are likely to provide cost-savings for the French NHI.