Citations

614 Background: A consensus interpretation of the IDEA colon cancer study results suggested that risk categories based on T/N stage grouping be used to guide decision-making for duration (3 vs 6 months) of adjuvant FOLFOX or CapeOX chemotherapy. Given the prognostic potential of immune biomarkers, we examined the immunoscore and individual T and B lymphocyte markers in low and high risk T/N subsets of stage III colon carcinoma patients (N=600) treated with adjuvant FOLFOX. Methods: Immunoscore (CD3+, CD8+) and individual T-cell and CD20+ B-cell immunostain densities in central tumor (CT) and invasive margin (IM) of FFPE sections were quantified by image analysis. A predetermined immunoscore categorization was used [high (2-4) vs low (0-1)]. Individual markers were analyzed by backwards selection wherein CD3+ IM was most robust for prognosis and an optimized cutoff was then determined. Associations with disease-free survival (DFS) were analyzed by multivariable Cox regression adjusting for age, T/N stage, sidedness, KRAS/BRAF, and DNA mismatch repair. Results: In low and high risk T/N patient subsets, the immunoscore and CD3+ IM were each significantly discriminant for prognosis. Among low risk (T1-3N1) patients, a high vs low immunoscore was associated with a 91% vs 77% 3-year DFS [HR 0.57, 95% confidence interval (CI) 0.34-0.95, adjusted (adj) P= 0.026]. Among high risk (T4 or N2) patients, a high vs low immunoscore was associated with a 68% vs 54% 3-year DFS (HR 0.64, 95% CI 0.42-0.98, Padj= 0.034]. Similarly, a high vs low intratumoral CD3+ density at the invasive margin (IM) was significantly associated with prognosis in low risk [HR 0.37, 95% CI 0.21- 0.66), Padj< 0.0003] and in high risk [HR 0.47, 95% CI, 0.27- 0.80), Padj< 0.0028] patient subsets. Conclusions: Immunoscore and CD3+ IM were shown to prognostically stratify FOLFOX-treated patients within both low and high risk T/N subsets. These data underscore limitations of the T/N risk classification for adjuvant treatment decisions in stage III patients, and demonstrate the ability of T-cell markers to enhance prognostication to guide clinical decision-making.

The prevalence of Lynch syndrome (LS) varies significantly in different populations, suggesting that ethnic features might play an important role. We enrolled 3330 consecutive Chinese patients who had surgical resection for newly diagnosed colorectal cancer. Universal screening for LS was implemented, including immunohistochemistry for mismatch repair (MMR) proteins, BRAFV600E mutation test and germline sequencing. Among the 3250 eligible patients, MMR protein deficiency (dMMR) was detected in 330 (10.2%) patients. Ninety‐three patients (2.9%) were diagnosed with LS. Nine (9.7%) patients with LS fulfilled Amsterdam criteria II and 76 (81.7%) met the revised Bethesda guidelines. Only 15 (9.7%) patients with absence of MLH1 on IHC had BRAFV600E mutation. One third (33/99) of the MMR gene mutations have not been reported previously. The age of onset indicates risk of LS in patients with dMMR tumors. For patients older than 65 years, only 2 patients (5.7%) fulfilling revised Bethesda guidelines were diagnosed with LS. Selective sequencing of all cases with dMMR diagnosed at or below age 65 years and only of those dMMR cases older than 65 years who fulfill revised Bethesda guidelines results in 8.2% fewer cases requiring germline testing without missing any LS diagnoses. While the prevalence of LS in Chinese patients is similar to that of Western populations, the spectrum of constitutional mutations and frequency of BRAFV600E mutation is different. Patients older than 65 years who do not meet the revised Bethesda guidelines have a low risk of LS, suggesting germline sequencing might not be necessary in this population.

Objective To summarise the available information on physician workforce modelling, to develop a rheumatology workforce prediction risk of bias tool and to apply it to existing studies in rheumatology. Methods A systematic literature review (SLR) was performed in key electronic databases (1946–2017) comprising an update of an SLR in rheumatology and a hierarchical SLR in other medical fields. Data on the type of workforce prediction models and the factors considered in the models were extracted. Key general as well as specific need/demand and supply factors for workforce calculation in rheumatology were identified. The workforce prediction risk of bias tool was developed and applied to existing workforce studies in rheumatology. Results In total, 14 studies in rheumatology and 10 studies in other medical fields were included. Studies used a variety of prediction models based on a heterogeneous set of need/demand and/or supply factors. Only two studies attempted empirical validation of the prediction quality of the model. Based on evidence and consensus, the newly developed risk of bias tool includes 21 factors (general, need/demand and supply). The majority of studies revealed high or moderate risk of bias for most of the factors. Conclusions The existing evidence on workforce prediction in rheumatology is scarce, heterogeneous and at moderate or high risk of bias. The new risk of bias tool should enable future evaluation of workforce prediction studies. This review informs the European League Against Rheumatism points to consider for the conduction of workforce requirement studies in rheumatology.