Risk and Prognosis of Subsequent Primary Gastric Cancer

Introduction: The incidence and prognostic impact of subsequent primary gastric cancer (GC) in a population of other cancer survivors is unclear. We aimed to evaluate susceptibility to subsequent primary GC in cancer survivors and prognosis of GC with prior cancer history. Methods: 2,211 and 23,416 GC cases with and without prior cancer history were retrospectively selected from the Surveillance, Epidemiology and End Results (SEER) database. Potential risk of developing subsequent primary GC was assessed through standardized incidence ratios (SIRs). Cox regression were adopted to analyze the influence of prior cancer history and clinical characteristic factors on the prognosis of subsequent primary GC. A nomogram was established to predict overall survival (OS). Propensity score matching (PSM) was conducted to eliminate possible bias. Results: Compared with general population, cancer survivors had an increased risk of subsequent primary GC (SIR 1.17, 95% CI 1.15-1.20, P<0.05). Prior cancer history was related to poor OS of GC [adjusted hazard ratio (aHR) 1.12, 95% CI 1.06-1.19, P<0.001], but not cancer-specific survival (aHR 0.97, 95% CI 0.89-1.05, P=0.441). In addition, age, grade, stage, year of diagnosis, surgery, TNM stage and tumor size were independent prognostic factors for OS in GC cases with prior cancers. The concordance index of the nomogram was 0.72 (95% CI 0.71-0.74), and calibrate curves showed good agreement between prediction by the nomogram and actual observation. Conclusions: Cancer survivors with increased risk of developing subsequent primary GC should strengthen their monitoring and follow-up to prevent occurrence of subsequent primary gastric cancer.

Generating Value from Mature Gas Fields by Quantifying Well Integrity Assurance with a Critical Analysis of Multiple Logs & Retrieved Tubular Surface Inspection

Sharjah National Oil Corporation (SNOC) operates 4 onshore gas condensate reservoirs of which 3 are very mature consisting of 50+ wells producing corrosive hydrocarbons for over 30 years. The integrity of these legacy wells is frequently questioned before any development is conceptualized, thus making it critical to evaluate the well integrity. The cost associated with pulling completions for their evaluation and running logs in all wells is significant and the availability of various emerging technologies for corrosion analysis in the market makes it challenging to choose the most reliable one. This paper focuses on the detailed analysis and comparison of electromagnetic thickness logs run in 10% of the well stock from 2016 to post-workover surface inspection of the downhole recovered tubing's in 2020/21. It also quantifies how correlating different logging technologies for well integrity increases the reliability of the electromagnetic technology applied on offset wells. The paper also showcases a comparison between mechanical and electromagnetic thickness evaluation of the production casing in-situ. Data from all the available logs from past 5 years was compiled for 6 wells. On recovery of the downhole completion tubings via a hydraulic workover, an ultrasonic (UT) inspection was performed on them at surface. Both sets of results (logs and surface inspection) were analyzed on the same logging track to give a comprehensive comparison of actual observation on surface vs the measurement by in-situ logging. Another multi-barrier corrosion and caliper log were run in the production casing to analyze their outcomes alongside older results. The final step was a comparison of all available data to create a broad well integrity profile. It was observed that the remaining production tubing metal thickness detected by electromagnetic tool (logs) and surface ultrasonic measurements were in good conformance (+/-10%). In the corrosion evaluation of the production casing, the electromagnetic tool matched extremely well with the caliper log results. This shows a large reliability of this technology to quantify corrosion in offset wells. The correlation of logs with surface inspection results across wells in the same reservoir did not indicate a strong presence of external corrosion. The study enables the management to make critical business decisions on utilizing the well stock for the future. This work is the first time a comprehensive and critical analysis on the electromagnetic thickness logging technology has been done, comparing their results of remaining wall thickness to various technologies in-situ and on surface. The analysis not only compares technology from various providers, but also mechanical vs electromagnetic measurements along with their respective advantages in quantifying well integrity assurance. The paper also gives an idea on the condition of L-80 tubulars under service for 30+ years.

Nomogram for Predicting Occurrence of Synchronous Liver Metastasis in Colorectal Cancer: A Single-center Retrospective Study Based on Pathological Factors

PurposeThe purpose of this study was to explore the risk factors for liver metastasis (LM) of colorectal cancer (CRC) and to construct a nomogram for predicting the occurrence of synchronous LM based on baseline and pathological information.MethodsThe baseline and pathological information of 3190 CRC patients from the Department of Colorectal Surgery, the Second Affiliated Hospital of Harbin Medical University between 2012 and 2020 were included. All patients were divided into development and validation cohorts with the 1:1 ratio. Univariate and multivariate logistic regression models were utilized to identify the potential predictors of LM in CRC patients. Using the R tool to create a predictive nomogram. In addition, receiver operating characteristic (ROC) curves was calculated to describe the discriminability of the nomogram. A calibration curve was plotted to compare the predicted and observed results of the nomogram. Decision-making curve analysis (DCA) was used to evaluate the clinical effect of nomogram.ResultsThe nomogram consisted of six features including tumor site, vascular invasion (VI), T stage, N stage, preoperative CEA and CA-199 level. ROC curves for the LM nomogram indicated good discrimination in the development cohort (AUC = 0.885, 95% CI 0.854-0.916) and the validation cohort (AUC = 0.857, 95% CI 0.821-0.893). The calibration curve showed that the prediction results of the nomogram was in good agreement with the actual observation results. Moreover, the DCA curves determined the clinical application value of predictive nomogram.ConclusionsThe pathologic-based nomogram could help clinicians to predict the occurrence of synchronous LM in postoperative CRC patients and provide a reference to perform appropriate metastatic screening plans and rational therapeutic options for the special population.

Development of a Nomogram for Predicting the Cumulative Incidence of Disease Recurrence of AML After Allo-HSCT

Using targeted exome sequencing, we studied correlations between mutations at diagnosis and transplant outcomes in 332 subjects with acute myeloid leukemia (AML) receiving allotransplantation. A total of 299 patients (299/332, 90.1%) had at least one oncogenic point mutation. In multivariable analyses, pretransplant disease status, minimal residual disease (MRD) before transplantation (pre-MRD), cytogenetic risk classification, and TP53 and FLT3-ITDhigh ratio mutations were independent risk factors for AML recurrence after allotransplantation (p &lt; 0.05). A nomogram for the cumulative incidence of relapse (CIR) that integrated all the predictors in the multivariable model was then constructed, and the concordance index (C-index) values at 6, 12, 18, and 24 months for CIR prediction were 0.754, 0.730, 0.715, and 0.690, respectively. Moreover, calibration plots showed good agreements between the actual observation and the nomogram prediction for the 6, 12, 18, and 24 months posttransplantation CIR in the internal validation. The integrated calibration index (ICI) values were 0.008, 0.055, 0.094, and 0.136 at 6, 12, 18, and 24 months posttransplantation, respectively. With a median cutoff score of 9.73 from the nomogram, all patients could be divided into two groups, and the differences in 2-year CIR, disease-free survival (DFS), and overall survival (OS) between these two groups were significant (p &lt; 0.05). Taken together, the results of our study indicate that gene mutations could help to predict the outcomes of patients with AML receiving allotransplantation.

Eye with Ears – A Symbol-Based Aid in Medical Teaching

Visual clinical examination forms the diagnostic basis in skin-related conditions and is an essential element in medical teaching. The author describes a symbol-based aid to explain the dichotomy of factual observed findings with the information based on medical history: The Eye with Ears. It represents the two most relevant aspects in clinical examination of skin-related conditions and helps to clarify the contrast between the actual observation with information based on the context or past medical history. With the described aid, the author believes to have improved the quality of the teaching in clinical examination and that it has functioned as a practical help for medical students’ and residents’ professional development.

A nomogram to predict stricture-free survival in patients with ureteral stricture after balloon dilation

Background Balloon dilation is a commonly used minimally invasive endourological treatment of ureteral stricture, but the postoperative recurrence rate is relatively high. And factors contributing to recurrence after treatment are poorly understood. Herein, we sought to develop a novel clinical nomogram to predict ureteral stricture-free survival in patients suffering from ureter stricture and performed balloon dilation. Methods The nomogram was established based on a retrospective analysis of 321 patients who received endoscopic balloon dilation alone for ureter strictures from January 2016 to January 2020 in Sun Yat-sen Memorial Hospital using the Cox regression model. Perioperative clinical data and disease outcomes were analyzed. The primary endpoint was the onset of ureteral re-stricture after ureter balloon dilation. Discrimination of the nomogram was assessed by the concordance index (C-index) and the calibration curve. The results were internally validated using bootstrap resampling. Results Overall, 321 patients with a median follow-up of 590 days were enrolled in the study, among which 97 patients (30.2%) developed recurrence of ureteral stricture during follow-up. Five variables remained significant predictors of ureteral re-stricture after multivariable analyses: stricture nature (P < 0.001), urinary nitrite (P = 0.041), CKD (P = 0.005), stent retention time (P < 0.001), and balloon size (P = 0.029). The calibration craves for the probability of 1-, 3-, and 5-years stricture-free survival (SFS) presented satisfied with the consistency of nomogram prediction and actual observation. The C-index of the model was 0.74 (95% CI 0.70–0.79). Conclusions Our study developed the first nomogram to effectively predict stricture-free survival in patients suffering from ureter stricture after balloon dilation. It is helpful to identify the optimal patients with ureter stricture for balloon dilation and improve treatment outcomes. However, further external validation of the nomogram is warranted.

Influence of Indirect Solar Irradiance on Satellite Observation

With the development of Space Domain Awareness(SDA), satellites’ optical characteristics are becoming attention-grabbing. Sunlight was usually considered the only light source for the satellites. However, in the actual observation, researchers have found that earthshine and moonlight would increase errors of the observation results, which have greatly influence the estimation of the satellite’s state. In order to avoid this influence, we propose an observation strategy. Firstly, we propose an accurate earthshine model, which considers the earth’s volume and favors long-time continuous satellite observation. Then, we explore the earthshine and moonlight’s impact on satellite observation results and find that this impact varies with the satellite attributes. Furthermore, we Figure out the law of this impact and establish a connection between this law and observation geometry. Finally, a Period Contribution model is proposed to provide a corresponding observation strategy to avoid the influence of earthshine and moonlight.

Optimal Age Group Selection and Development of a Nomogram To Predict Complications in Patients Undergoing Simultaneous Bilateral Total Knee Arthroplasty

Purpose By comparing the occurrence of complications at 30 days after Simultaneous bilateral total knee arthroplasty (SBTKA) for each age group, the optimal age range of patients receiving SBTKA was determined.An individualized histogram model was established to predict complications within 30 days after SBTKA. Methods The general data of 861 patients who received SBTKA in our hospital on January 1, 2012 and March 31, 2017 were retrospectively analyzed. According to the age of the patients, they were divided into four ages: less than 60 years old, 60 to 64 years old, 65 to 69 years old and over 70 years old. The incidence of complications in different ages was studied.According to the occurrence of complications, 96 cases were included in the complication group and 765 cases in the non-complication group. Univariate and multivariate Logistic regression analysis was conducted to determine and screen out the independent risk factors for complications after SBTKA, and then R software was used to construct the prediction model of the nomogram.The area under the curve (AUC), calibration curve, and decision curve analysis (DCA) were selected to evaluate the nomogram. Results Patients aged 60 to 64 years had the lowest overall postoperative complication rate (7.17%).Five independent predictors were identified by multivariate analysis and were used to establish the nomogram.The AUC of the nomogram was 0.851(95%CI:0.819–0.883).The calibration curve showed that the prediction of nomogram was highly consistent with the actual observation, and DCA showed that nomogram had good clinical usefulness. Conclusion The optimal age group for SBTKA is between 60 and 64 years of age, where the incidence of complications is lowest.Older age, lower preoperative hemoglobin levels, higher preoperative blood urea nitrogen(BUN) levels, longer operation time, and ASA grade ≥ III were identified as independent predictors of complications within 30 days after SBTKA.A nomogram containing the above five predictors could accurately predict the risk of complications within 30 days after SBTKA.

Prognostic Value of Combined Preoperative Carcinoembryonic Antigen and Prognostic Nutritional Index in Patients With Stage II–III Colon Cancer

Background: Tumor status can affect patient prognosis. Prognostic nutritional index (PNI), as a nutritional indicator, is closely related to the prognosis of cancer. However, few studies have examined the combined prognostic value of CEA and PNI in patients. This study investigated the relationship between CEA/PNI and prognosis of colon cancer patients.Methods: A total of 513 patients with stage II–III colon cancer who underwent curative resection at two medical centers from 2009 to 2019 were included. Clinicopathological factors were assessed and overall survival (OS) was assessed in a cohort of 413 patients. Multivariate analysis was used to identify independent prognostic variables to construct histograms predicting 1-year and 3-year OS. Data from 100 independent patients in the validation group was used to validate the prognostic model.Results: The median OS time was 33.6 months, and mortality was observed in 54 patients. Multivariate analysis revealed that preoperative CEA/PNI, lymph node metastasis, peripheral nerve invasion, operation mode, and postoperative chemotherapy were independent factors for prognosis evaluation and thus were utilized to develop the nomogram. The C-index was 0.788 in the learning set and 0.836 in the validation set. The calibration curves reached favorable consensus among the 1-, 3-year OS prediction and actual observation.Conclusion: The combined use of CEA and PNI is an independent prognostic factor and thus can serve as a basis for a model to predict the prognosis of patients with stage II–III colon cancer.

Early Anomaly Detection Model Using Random Forest while Drilling Horizontal Wells with a Real Case Study

There has been discrepancy between the pre-calculated and actual T&D values, because of the dependence of the model’s predictability on assumed inputs. Therefore, to have a reliable model, the users must adjust the model inputs; mainly friction coefficient in order to match the actual T&D. This, however, can mask downhole conditions such as cutting beds, tight holes and sticking tendencies. This paper aims to introduce a machine learning model to predict the continuous profile of the surface drilling torque to detect the operational issues in advance. Actual data of Well-1, starting from the time of drilling a 5-7/8-inch horizontal section until one day prior to the stuck pipe event, was used to train and test a random forest (RF) model with an 80/20 split ratio, to predict the surface drilling torque. The input variables for the model are the drilling surface parameters, namely: flow rate, hook load, rate of penetration, rotary speed, standpipe pressure, and weight-on-bit. The developed model was used to predict the surface drilling torque, which represents the normal trend for the last day leading up to the stuck pipe incident in Well-1. Then the model was integrated with a multivariate metric distance, Mahalanobis, to be used as a classifier to measure how close an actual observation is from the predictive normal trend. Based on a pre-determined threshold, each actual observation was labeled as "NORMAL" or "ANOMAL".