The development and validation of a nomogram for predicting brain metastases after chemotherapy and radiotherapy in male small cell lung cancer patients with stage III.

OBJECTIVE: The purpose of this research was to develop a model for brain metastasis (BM) in limited-stage small cell lung cancer (LS-SCLC) patients and to help in the early identification of high-risk patients and the selection of individualized therapies. METHODS: Univariate and multivariate logic regression was applied to identify the independent risk factors of BM. A receiver operating curve (ROC) and nomogram for predicting the incidence of BM were then conducted based on the independent risk factors. The decision curve analysis (DCA) was performed to assess the clinical benefit of prediction model. RESULTS: Univariate regression analysis showed that the CCRT, RT dose, PNI, LLR, and dNLR were the significant factors for the incidence of BM. Multivariate analysis showed that CCRT, RT dose, and PNI were independent risk factors of BM and were included in the nomogram model. The ROC curves revealed the area under the ROC (AUC) of the model was 0.764 (95% CI, 0.658-0.869), which was much higher than individual variable alone. The calibration curve revealed favorable consistency between the observed probability and predicted probability for BM in LS-SCLC patients. Finally, the DCA demonstrated that the nomogram provides a satisfactory positive net benefit across the majority of threshold probabilities. CONCLUSIONS: In general, we established and verified a nomogram model that combines clinical variables and nutritional index characteristics to predict the incidence of BM in male SCLC patients with stage III. Since the model has high reliability and clinical applicability, it can provide clinicians with theoretical guidance and treatment strategy making.

Predictive value of monocytes and lymphocytes for short-term neutrophil changes in chemotherapy-induced severe neutropenia in solid tumors.

PURPOSE: To explore whether monocytes, lymphocytes, and platelets have a predictive value for short-term neutrophil changes in patients with severe neutropenia (SN) induced by chemotherapy. METHODS: Complete blood counts (CBC) were collected from a total of 62 patients with chemotherapy-induced SN from December 2013 to March 2018. CBCs at intervals of 1 day, 2 days, 3 days, 4 days, and 5 days were recorded, and logistic regression analyses were performed to determine whether the monocyte percentage (MP), absolute monocyte count (AMC), lymphocyte percentage (LP), absolute lymphocyte count (ALC), or platelet count (PC) were correlated with short-term neutrophil changes. The areas under the receiver operating characteristic (ROC) curves (AUCs) were calculated for parameters with a P value < 0.05. RESULTS: The MP was significantly correlated with changes in neutrophils for intervals of 1 to 5 days, while the LP was significantly correlated with changes in neutrophils for intervals of 2 to 5 days. A cutoff value of 6.5% for the MP yielded a sensitivity of 80%, a specificity of 88.6%, and an AUC of 0.908 for predicting an increase in neutrophils on the third day. A cutoff value of 14.75% for the LP yielded a sensitivity of 93.3%, a specificity of 70.3%, and an AUC of 0.812 for predicting an increase in neutrophils on the sixth day. CONCLUSIONS: In chemotherapy-induced neutropenia patients, the MP is the best predictor of short-term neutrophil changes. Close monitoring and proper interpretation of the MP and LP are informative in managing chemotherapy-induced neutropenia.

Survival benefit of re-irradiation in esophageal Cancer patients with Locoregional recurrence: a propensity score-matched analysis.

BACKGROUND: To investigate the treatment failure pattern and factors influencing locoregional recurrence of esophageal squamous cell carcinoma (ESCC) and examine patient survival with re-irradiation (re-RT) after primary radiotherapy. METHODS: We retrospectively analyzed 87 ESCC patients treated initially with radiotherapy. Failure patterns were classified into regional lymph node recurrence only (LN) and primary failure with/without regional lymph node recurrence (PF). Patients received either re-RT or other treatments (non-re-RT group). Baseline covariates were balanced by a propensity score model. Overall survival (OS) and toxicities were assessed as outcomes. RESULTS: The median follow-up time was 87 months. Thirty-nine patients received re-RT. Failure pattern and re-RT were independent prognostic factors for OS (P = 0.040 and 0.015) by Cox multivariate analysis. Re-RT with concomitant chemotherapy showed no survival benefit over re-RT alone (P = 0.70). No differences in characteristics were found between the groups by Chi-square tests after propensity score matching. The Cox model showed that failure pattern and re-RT were prognostic factors with hazard ratios (HR) of 0.319 (P = 0.025) and 0.375 (P = 0.002), respectively, in the matched cohort. Significant differences in OS were observed according to failure pattern (P = 0.004) and re-RT (P < 0.001). In the re-RT and non-re-RT groups, 9.09% and 3.03% of patients experienced tracheoesophageal fistulas, and 15.15% and 3.03% of patients developed pericardial/pleural effusion, respectively (P > 0.05). The incidence of radiation pneumonitis was higher in the re-RT group (24.24% vs. 6.06%, P = 0.039), but no cases of pneumonia-related death occurred. CONCLUSIONS: Re-RT improved long-term survival in patients with locoregional recurrent ESCC. Despite a high incidence of radiation pneumonitis, toxicities were tolerable.

Constructing three-dimensional detachable and composable computer models of the head and neck.

The head and neck region has a complex spatial and topological structure, three-dimensional (3D) computer model of the region can be used in anatomical education, radiotherapy planning and surgical training. However, most of the current models only consist of a few parts of the head and neck, and the 3D models are not detachable and composable. In this study, a high-resolution 3D detachable and composable model of the head and neck was constructed based on computed tomography (CT) serial images. First, fine CT serial images of the head and neck were obtained. Then, a color lookup table was created for 58 structures, which was used to create anatomical atlases of the head and neck. Then, surface and volume rendering methods were used to reconstruct 3D models of the head and neck. Smoothing and polygon reduction steps were added to improve 3D rendering effects. 3D computer models of the head and neck, including the sinus, pharynx, vasculature, nervous system, endocrine system and glands, muscles, bones and skin, were reconstructed. The models consisted of 58 anatomical detachable and composable structures and each structure can be displayed individually or together with other structures.

Long-term follow-up and prognostic factors for advanced thymic carcinoma.

The aim of this study was to evaluate the long-term survival outcomes in patients with advanced thymic carcinoma and identify prognostic factors influencing the survival. We retrospectively analyzed 90 consecutive patients with pathologically confirmed advanced thymic carcinoma (Masaoka III and IV) in our institute, from December 2000 to 2012. Age, sex, clinical characteristics, laboratory findings, Masaoka and tumor node metastasis staging, pathologic grade, and treatment modalities were analyzed to identify prognostic factors associated with the progress-free survival (PFS) and the overall survival (OS) rates. Statistical analysis was conducted using SPSS, version 19.0 (SPSS, Inc, Chicago, IL). A total of 73 (81.1%) male and 17 (18.9%) female patients participated in the study. The median follow-up time was 75 months (range, 20-158 months). The 5-year PFS and OS rates were 23.6% (95% confidence interval [CI], 14.6%-33.8%) and 35.7% (95% CI, 25.1%-46.4%), respectively. The multivariate Cox regression model analysis showed that factors improving the PFS were the normal lactate dehydrogenase (LDH) level (P<0.001), Masaoka III stage (P=0.028), and radiotherapy (RT) (P<0.001). The LDH (P<0.001), T stage (P<0.001), and the pathologic grade (P=0.047) were independently prognostic of OS. Long-term follow-up of the advanced thymic carcinoma showed poor outcomes of PFS and OS. LDH, Masaoka stage, and RT affected the PFS, and LDH, T stage, and pathologic grade seemed to affect the OS. Establishing a better staging system for predicting outcomes would be warranted.

The effects of the shape and size of the clinical target volume on the planning target volume margin.

PURPOSE: To investigate the impact of clinical target volume (CTV) shape and size on CTV to planning target volume (PTV) margin expansion. METHODS AND MATERIALS: Using numerical integration methods, margins accounting for random errors and systematic errors were calculated for CTVs of different shapes and sizes. We use k(r-95) and k(s-95) to represent the coefficients, for random errors and systematic errors, respectively, that ensure that every point of the CTV receives ≥95% of the prescribed dose. RESULTS: The part of the margin accounting for random errors depends on CTV shape and size; generally, a convex part of a CTV would have a larger margin than a concave part. However, the part of the margin accounting for systematic errors is independent of CTV shape and size. CONCLUSIONS: CTV shape and size should be considered when generating a PTV. For a complex CTV, the margins of the various parts of the CTV are different and related to local forms.

On the consistent measurement of attainment and shortfall inequality.

In measuring inequality of a bounded variable such as health status, one can focus on attainments or shortfalls. However, rankings of social states by attainment and shortfall inequality do not necessarily mirror one another. We propose a requirement, that attainment inequality and shortfall inequality be measured consistently, and we examine the performance of partial orderings and indices of inequality in this respect. For relative inequality and all currently documented intermediate inequality concepts, the orderings fail our consistency requirement, as do all indices which respect these orderings. However, the absolute inequality partial ordering satisfies consistency. We identify two classes of indices of absolute inequality, one containing rank-independent and the other rank-dependent indices, which measure attainment and shortfall inequality consistently (in fact identically). The only subgroup decomposable inequality index, of any type, which measures attainment and shortfall inequality consistently is the variance. We discuss implications for the study of pure health inequality.

[Measurement of setup error in conformal radiotherapy for nasopharyngeal carcinoma].

BACKGROUND & OBJECTIVE: Setup error is the key factor in determining the margin of planning target volume (M(PTV)) for conformal radiotherapy of nasopharyngeal carcinoma (NPC). This study was to establish a method using radiopaque fiducial markers which were embedded in occlusal splint ("occlusal splint method") to acquire setup errors to calculate M(PTV) in CRT for NPC. METHODS: The occlusal splint method was performed in 22 NPC patients who received CRT. Setup errors were calculated by comparing the coordinates of 3 fiducial markers read from portal images with those read from computed tomography (CT) data. According to the formulation, the size of MPTV with or without consideration of organ motion was also calculated. RESULTS: The standard deviations of systematic errors (Sigma) were 1.13 mm, 1.47 mm, and 1.31 mm in X (medio-lateral), Y (antero-posterior) and Z (cranio-caudal) axes, respectively; the standard deviations of random errors were 0.81 mm, 0.45 mm, and 0.80 mm in X, Y, and Z axes, respectively. Without consideration of organ motion, the sizes of M(PTV) were 3.40 mm, 3.98 mm, and 3.83 mm in X, Y, and Z axes, respectively; with consideration of organ motion, the sizes of M(PTV) were 3.75 mm, 4.35 mm, and 4.16 mm in X, Y, and Z axes, respectively. CONCLUSION: Using the "occlusal splint method", each institution can precisely calculate setup error data, and stipulate the size of M(PTV) adequate to one's own situation.