ABSTRACT
Purpose: To establish a predictive model to predict the occurrence of language deficit for patients after surgery of glioma involving language areas (GILAs) under general anesthesia (GA). Methods: Patients with GILAs were retrospectively collected in our center between January 2009 and December 2020. Clinical variables (age, sex, aphasia quotient [AQ], seizures and KPS), tumor-related variables (recurrent tumor or not, volume, language cortices invaded or not, shortest distance to language areas [SDLA], supplementary motor area or premotor area [SMA/PMA] involved or not and WHO grade) and intraoperative multimodal techniques (used or not) were analyzed by univariate and multivariate analysis to identify their association with temporary or permanent language deficits (TLD/PLD). The predictive model was established according to the identified significant variables. Receiver operating characteristic (ROC) curve was used to assess the accuracy of the predictive model. Results: Among 530 patients with GILAs, 498 patients and 441 patients were eligible to assess TLD and PLD respectively. The multimodal group had the higher EOR and rate of GTR than conventional group. The incidence of PLD was 13.4% in multimodal group, which was much lower than that (27.6%, P<0.001) in conventional group. Three factors were associated with TLD, including SDLA (OR=0.85, P<0.001), preoperative AQ (OR=1.04, P<0.001) and multimodal techniques used (OR=0.41, P<0.001). Four factors were associated with PLD, including SDLA (OR=0.83, P=0.001), SMA/PMA involved (OR=3.04, P=0.007), preoperative AQ (OR=1.03, P=0.002) and multimodal techniques used (OR=0.35, P<0.001). The optimal shortest distance thresholds in detecting the occurrence of TLD/PLD were 1.5 and 4mm respectively. The optimal AQ thresholds in detecting the occurrence of TLD/PLD were 52 and 61 respectively. The cutoff values of the predictive probability for TLD/PLD were 23.7% and 16.1%. The area under ROC curve of predictive models for TLD and PLD were 0.70 (95%CI: 0.65-0.75) and 0.72 (95%CI: 0.66-0.79) respectively. Conclusion: The use of multimodal techniques can reduce the risk of postoperative TLD/PLD after removing GILAs under general anesthesia. The established predictive model based on clinical variables can predict the probability of occurrence of TLD and PLD, and it had a moderate predictive accuracy.
ABSTRACT
Purpose: To explore molecular alterations and their correlation with the survival of patients with glioblastoma (GBM) with corpus callosum (CC) involvement (ccGBM). Methods: Electronic medical records were reviewed for glioma patients tested for molecular alterations and treated at our hospital between January 2016 and July 2020. ccGBM was compared to GBM without CC involvement (non-ccGBM) to identify differences in molecular alterations. Clinical outcomes and survival were compared between ccGBM and non-ccGBM patients, as well as among patients with ccGBM with different molecular alteration statuses. ccGBM was also compared to diffuse midline glioma (DMG) to clarify their correlation in molecular alterations, the progression-free survival (PFS), and overall survival (OS). Results: Thirty ccGBM and 88 non-ccGBM patients were included. PDGFRA amplification (PDGFRAamp, 33.3 vs. 9.1%, P = 0.004) and missense mutation (PDGFRAmut, 20.0 vs. 3.4%, P = 0.011) both had higher incidences in ccGBM than in non-ccGBM. PDGFRA alteration was associated with the occurrence of ccGBM (OR = 4.91 [95% CI: 1.55-15.52], P = 0.007). ccGBM with PDGFRAamp resulted in a shorter median PFS (8.6 vs. 13.5 months, P = 0.025) and OS (12.4 vs. 17.9 months, P = 0.022) than non-ccGBM with PDGFRAnon-amp. ccGBM with PDGFRAamp combined with PDGFRAmut (PDGFRAamp-mut) had a shorter median PFS (7.6 vs. 8.9 months, P = 0.022) and OS (9.6 vs. 17.8 months, P = 0.006) than non-ccGBM with wild-type PDGFRA and no amplification (PDGFRA-w, non-amp). Compared to ccGBM with PDGFRA-w, non-amp, ccGBM with PDGFRAamp and PDGFRAamp-mut both had a shorter median PFS and OS (P < 0.05). The hazard ratios (HRs) of PDGFRAamp for PFS and OS in ccGBM were 3.08 (95% CI: 1.02-9.35, P = 0.047) and 5.07 (1.52-16.89, P = 0.008), respectively, and the HRs of PDGFRAamp-mut for PFS and OS were 13.16 (95% CI: 3.19-54.40, P < 0.001) and 16.36 (2.66-100.70, P = 0.003). ccGBM may have similar incidences of PDGFRAamp or mut (PDGFRAamp/mut) as DMG, and they also had similar median PFS (10.9 vs. 9.0 months, P = 0.558) and OS (16.8 vs. 11.5 months, P = 0.510). Conclusion: PDGFRA alterations are significantly associated with the occurrence and poor prognosis of ccGBM. ccGBM with PDGFRAamp/mut may be classified as a single subtype of GBM that has a similar survival rate to DMG. PDGFR inhibitors may be a promising treatment method for ccGBM.
ABSTRACT
BACKGROUND: The trends in usage of tumor markers, including CEA, SCC, NSE, Cyfra21-1, and ProGRP, in Chinese lung cancer patients in the real-world setting are not fully investigated. METHODS: A retrospective descriptive study was conducted using the database of Qilu Hospital of Shandong University, China between January 2013 and December 2017, involving patients primarily diagnosed with NSCLC or SCLC. Utilization trends by first discharge year, utilization rates within different durations before and after first discharge date, and combined utilization patterns of multiple tumor markers were analyzed. RESULTS: The utilization of all these tumor markers showed increased from 2013 to 2017. CEA, Cyfra21-1, and NSE were the most frequently detected, which increased slightly from around 50% in 2013 to around 78% in 2017 in NSCLC and from around 70% in 2013 to around 92% in 2017 in SCLC. CEA, Cyfra21-1, and NSE were the most commonly measured within 3 months before first diagnosis with approximately 65% in NSCLC and 80% in SCLC, and ProGRP had the lowest utilization (around 30%). CEA, NSE, and Cyfra21-1 had the highest utilization rates after first diagnosis with both around 80% in NSCLC or SCLC. Combined usage of five tumor markers was ranked the first pattern in combined utilization. CONCLUSIONS: This study suggests CEA, Cyfra21-1, and NSE are the most frequently detected before or after first diagnosis of NSCLC or SCLC. However, SCC and ProGRP tests appeared to have relatively low usages. The utilization pattern was consistent with recommendations of guideline, but underutilization still existed.
