Impact of COVID-19 social distancing measures on lung transplant recipients: decline in overall respiratory virus infections is associated with stabilisation of lung function.

BACKGROUND: Coronavirus disease 2019 (COVID-19) social distancing measures led to a dramatic decline in non-COVID-19 respiratory virus infections, providing a unique opportunity to study their impact on annual forced expiratory volume in 1 s (FEV1) decline, episodes of temporary drop in lung function (TDLF) suggestive of infection and chronic lung allograft dysfunction (CLAD) in lung transplant recipients (LTRs). METHODS: All FEV1 values of LTRs transplanted between 2009 and April 2020 at the University Medical Center Groningen (Groningen, The Netherlands) were included. Annual FEV1 change was estimated with separate estimates for pre-social distancing (2009-2020) and the year with social distancing measures (2020-2021). Patients were grouped by individual TDLF frequency (frequent/infrequent). Respiratory virus circulation was derived from weekly hospital-wide respiratory virus infection rates. Effect modification by TDLF frequency and respiratory virus circulation was assessed. CLAD and TDLF rates were analysed over time. RESULTS: 479 LTRs (12 775 FEV1 values) were included. Pre-social distancing annual change in FEV1 was -114 (95% CI -133- -94) mL, while during social distancing FEV1 did not decline: 5 (95% CI -38-48) mL (difference pre-social distancing versus during social distancing: p<0.001). The frequent TDLF subgroup showed faster annual FEV1 decline compared with the infrequent TDLF subgroup (-150 (95% CI -181- -120) versus -90 (95% CI -115- -65) mL; p=0.003). During social distancing, we found significantly lower odds for any TDLF (OR 0.53, 95% CI 0.33-0.85; p=0.008) and severe TDLF (OR 0.34, 0.16-0.71; p=0.005) as well as lower CLAD incidence (OR 0.53, 95% CI 0.27-1.02; p=0.060). Effect modification by respiratory virus circulation indicated a significant association between TDLF/CLAD and respiratory viruses. CONCLUSIONS: During COVID-19 social distancing the strong reduction in respiratory virus circulation coincided with markedly less FEV1 decline, fewer episodes of TDLF and possibly less CLAD. Effect modification by respiratory virus circulation suggests an important role for respiratory viruses in lung function decline in LTRs.

Addition of tumor microenvironment immune cell composition to improve the performance of a predictive model for oral squamous cell carcinoma.

BACKGROUND: Conventional clinicopathological characteristics insufficiently predict prognosis in oral squamous cell carcinoma (OSCC). We aimed to assess the added predictive value of tumor microenvironment immune cell composition (TMICC) in addition to conventional clinicopathological characteristics. METHODS: Primary tumor samples of 290 OSCC patients were immunohistochemically stained for CD4, CD8, CD20, CD68, CD163, CD57, FoxP3 and Programmed cell Death Ligand 1. Additionally, clinicopathological characteristics were obtained from patients' medical files. Predictive models were trained and validated by conducting Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses with cross-validation. To quantify the added predictive power of TMICC within models, receiver operating characteristic (ROC) analyses were used. RESULTS: Recurrence occurred in 74 patients (25.5%). Conventional clinicopathological characteristics (tumor localization, pathological T-stage, pathological N-stage, extracapsular spread, resection margin, differentiation grade, perineural invasion, lymphovascular invasion) and treatment modality, were used to build a LASSO logistic regression-based predictive model. Addition of TMICC to the model resulted in a comparable AUC of respectively 0.79 (±0.01) and 0.76 (±0.1) in the training and test sets. The model indicated that high numbers of CD4+ T cells protected against recurrence. Lymph node metastasis, extracapsular spread, perineural invasion, positive surgical margins and reception of adjuvant treatment were associated with increased risk for recurrence. CONCLUSIONS: The TMICC, specifically the number of CD4+ T cells, is an independent predictor , however, addition to conventional clinicopathological characteristics does not improve the performance of a predictive model for recurrence in OSCC.