Nomograms to Predict Recurrence-Free and Overall Survival After Curative Resection of Adrenocortical Carcinoma

A nomogram for predicting disability-free survival in older adults over 15 years: A population-based cohort study

BACKGROUND

This article aimed to develop and validate a simple-to-use nomogram to predict 15-year disability-free survival among older adults.

METHODS

A cohort of 1878 disability-free participants aged ≥60 was followed for 15 years. Participants were randomly divided into a training cohort for nomogram development (n = 1314 [70 %]) and validation cohort to confirm the model's performance (n = 564 [30 %]). Information on socio-demographic, lifestyle factors, the Life Satisfaction Index A (LSI-A), chronic diseases, and Mini-Mental State Examination (MMSE) score, and biomarkers were collected through interviews, clinical and neuropsychological examinations, and medical records. Disability-free survival was defined as survival in the absence of dementia and physical disability, and the composite endpoint is first occurrence of events of death, dementia and physical disability. We developed a nomogram summing the number of risk points corresponding to weighted covariates to predict disability-free survival. Validation of the nomogram using C statistic, calibration plots, and Kaplan-Meier curves.

RESULTS

In the multivariate-adjusted model, factors associated with composite end point were younger age, high MMSE (hazard ratio [HR], 0.93; [95 % CI, 0.87-0.99]), high LSI-A (0.78, [0.64-0.97]), non-smoking (0.74, [0.59-0.94]), engagement in physical leisure activity (0.62, [0.48-0.78]), and absence of chronic diseases (0.78, [0.66-0.91]). Incorporating these 6 factors, the nomogram achieved C-statistics of 0.78 (95 % CI, 0.75-0.81) and 0.77 (95 % CI, 0.74-0.80) in predicting disability-free survival in the training and validation cohorts, respectively, and had good calibration curves.

CONCLUSION

The nomogram was able to predict long-term of disability-free survival and performed well on internal validation, and may be considered for use in effective surveillance, promote, management of clinical and public health ageing.

Prognostic nomogram to predict cancer-specific survival with small-cell carcinoma of the prostate: a multi-institutional study

Objective

The aim of this study is to examine the predictive factors for cancer-specific survival (CSS) in patients diagnosed with Small-Cell Carcinoma of the Prostate (SCCP) and to construct a prognostic model.

Methods

Cases were selected using the Surveillance, Epidemiology, and End Results (SEER) database. The Kaplan-Meier method was utilized to calculate survival rates, while Lasso and Cox regression were employed to analyze prognostic factors. An independent prognostic factor-based nomogram was created to forecast CSS at 12 and 24 months. The model's predictive efficacy was assessed using the consistency index (C-index), calibration curve, and decision curve analysis (DCA) in separate tests.

Results

Following the analysis of Cox and Lasso regression, age, race, Summary stage, and chemotherapy were determined to be significant risk factors (P < 0.05). In the group of participants who received training, the rate of 12-month CSS was 44.6%, the rate of 24-month CSS was 25.5%, and the median time for CSS was 10.5 months. The C-index for the training cohort was 0.7688 ± 0.024. As for the validation cohort, it was 0.661 ± 0.041. According to the nomogram, CSS was accurately predicted and demonstrated consistent and satisfactory predictive performance at both 12 months (87.3% compared to 71.2%) and 24 months (80.4% compared to 71.7%). As shown in the external validation calibration plot, the AUC for 12- and 24-month is 64.6% vs. 56.9% and 87.0% vs. 70.7%, respectively. Based on the calibration plot of the CSS nomogram at both the 12-month and 24-month marks, it can be observed that both the actual values and the nomogram predictions indicate a predominantly stable CSS. When compared to the AJCC staging system, DCA demonstrated a higher level of accuracy in predicting CSS through the use of a nomogram.

Conclusion

Clinical prognostic factors can be utilized with nomograms to forecast CSS in Small-Cell Carcinoma of the Prostate (SCCP).

Development and validation of models for predicting preterm birth and gestational latency following emergency cervical cerclage: A multicenter cohort study

INTRODUCTION

Emergency cervical cerclage is a recognized method for preventing mid-trimester pregnancy loss and premature birth; however, its benefits remain controversial. This study aimed to establish preoperative models predicting preterm birth and gestational latency following emergency cervical cerclage in singleton pregnant patients with a high risk of preterm birth.

MATERIAL AND METHODS

We retrospectively reviewed data from patients who received emergency cerclage between 2015 and 2023 in three institutions. Patients were grouped into a derivation cohort (n = 141) and an independent validation cohort (n = 61). Univariate and multivariate logistic and Cox regression analyses were used to identify independent predictive variables and establish the models. Harrell's C-index, time-dependent receiver operating characteristic curves and areas under the curves, calibration curve, and decision curve analyses were performed to assess the models.

RESULTS

The models incorporated gestational weeks at cerclage placement, history of prior second-trimester loss and/or preterm birth, cervical dilation, and preoperative C-reactive protein level. The C-index of the model for predicting preterm birth before 28 weeks was 0.87 (95% CI: 0.82-0.93) in the derivation cohort and 0.82 (95% CI: 0.71-0.92) in the independent validation cohort; The C-index of the model for predicting gestational latency was 0.70 (95% CI: 0.66-0.75) and 0.78 (95% CI: 0.71-0.84), respectively. In the derivation set, the areas under the curves were 0.84, 0.81, and 0.84 for predicting 1-, 3- and 5-week pregnancy prolongation, respectively. The corresponding values for the external validation were 0.78, 0.78, and 0.79, respectively. Calibration curves showed a good homogeneity between the observed and predicted ongoing pregnant probabilities. Decision curve analyses revealed satisfactory clinical usefulness.

CONCLUSIONS

These novel models provide reliable and valuable prognostic predictions for patients undergoing emergency cerclage. The models can assist clinicians and patients in making personalized clinical decisions before opting for the cervical cerclage.

Prediction model for EBV infection following HLA haploidentical matched hematopoietic stem cell transplantation

AIMS

Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is an effective treatment for hematological malignancies. However, viral infections, particularly EBV infection, frequently occur following allo-HSCT and can result in multi-tissue and organ damage. Due to the lack of effective antiviral drugs, these infections can even progress to post-transplant lymphoproliferative disorders (PTLD), thereby impacting the prognosis. In light of this, our objective is to develop a prediction model for EBV infection following allo-HSCT.

METHODS

A total of 466 patients who underwent haploidentical hematopoietic stem cell transplantation (haplo-HSCT) between September 2019 and December 2020 were included in this study. The patients were divided into a development cohort and a validation cohort based on the timing of their transplantation. Our aim was to develop and validate a grading scale using these cohorts to predict the risk of EBV infection within the first year after haplo-HSCT. Additionally, single-cell RNA sequencing (sc-RNAseq) data from the bone marrow of healthy donors were utilized to assess the impact of age on immune cells and viral infection.

RESULTS

In the multivariate logistic regression model, four predictors were retained: donor age, female-to-male transplant, graft MNC (mononuclear cell) dose, and CD8 dose. Based on these predictors, an EBV reactivation predicting score system was constructed. The scoring system demonstrated good calibration in both the derivation and validation cohorts, as confirmed by the Hosmer-Lemeshow test (p > 0.05). The scoring system also exhibited favorable discriminative ability, as indicated by the C statistics of 0.72 in the derivation cohort and 0.60 in the validation cohort. Furthermore, the clinical efficacy of the scoring system was evaluated using Kaplan-Meier curves based on risk ratings. The results showed significant differences in EBV reactivation rates between different risk groups, with p-values less than 0.001 in both the derivation and validation cohorts, indicating robust clinical utility. The analysis of sc-RNAseq data from the bone marrow of healthy donors revealed that older age had a profound impact on the quantity and quality of immune subsets. Functional enrichment analysis highlighted that older age was associated with a higher risk of infection. Specifically, CD8 + T cells from older individuals showed enrichment in the pathway of "viral carcinogenesis", while older CD14 + monocytes exhibited enrichment in the pathway of "regulation of viral entry into host cell." These findings suggest that older age may contribute to an increased susceptibility to viral infections, as evidenced by the altered immune profiles observed in the sc-RNAseq data.

CONCLUSION

Overall, these results demonstrate the development and validation of an effective scoring system for predicting EBV reactivation after haplo-HSCT, and provide insights into the impact of age on immune subsets and viral infection susceptibility based on sc-RNAseq analysis of healthy donors' bone marrow.

Validated predictive model for treatment and prognosis of adrenocortical carcinoma

BACKGROUND

Adrenocortical carcinoma has a poor prognosis and multiple clinical, pathological, and treatment variables. Currently, we lack a prognostic and treatment calculator to determine the survival and efficacy of adjuvant chemoradiation. We aimed to validate a calculator to assess prognosis and treatment.

METHODS

We searched the National Cancer Database to identify patients with adrenocortical carcinoma surgically treated from 2004 to 2020 and randomly allocated them into a training (80%) or validation set (20%). We analyzed the variables of age; sex; Charlson Comorbidity Index; insurance status; tumor size; pathologic tumor, node, and metastasis categories; surgical margins; and use of chemotherapy and radiation therapy. We used Cox regression prediction models and bootstrap coefficients to generate a mathematical model to predict 5- and 10-year overall survival. After using the area under the curve analysis to assess the model's performance, we compared overall survival in the training and validation sets.

RESULTS

Multivariable analysis of the 3,480 patients included in the study revealed that all variables were significant except sex (P < .05) and incorporated into a mathematical model. The area under the curve for 5- and 10-year overall survival was 0.68 and 0.70, respectively, for the training set and 0.70 and 0.72, respectively, for the validation set. For the bootstrap coefficients, the 5- and 10-year overall survival was 6.4% and 4.1%, respectively, above the observed mean.

CONCLUSION

Our model predicts the overall survival of patients with adrenocortical carcinoma based on clinical, pathologic, and treatment variables and can assist in individualizing treatment.

Contrast CT radiomic features add value to prediction of prognosis in adrenal cortical carcinoma

OBJECTIVE

Adrenocortical carcinoma (ACC) is a rare and aggressive malignancy with poor prognosis due to high postoperative recurrence rates. The aim of this study is to develop a contrast CT radiomic feature-based prognosis prediction model for ACC and evaluate its performance by comparison with ENSAT staging system and S-GRAS score.

METHODS

Included in this study were 39 ACC patients, from which we extracted 1411 radiomic features. Using cross-validated least absolute shrinkage and selection operator regression (cv-LASSO regression), we generated a radiomic index. Additionally, we further validated the radiomic index using both univariate and multivariate Cox regression analyses. We constructed a radiomic nomogram that incorporated the radiomic signature and compared it with ENSAT stage and S-GRAS score in terms of calibration, discrimination and clinical usefulnes.

RESULTS

In this study, the average progression free survival (PFS) of 39 patients was 20.4 (IQR 9.1-60.1) months and the average overall survival (OS) was 57.8 (IQR 32.4-NA). The generated radiomic features were significantly associated with PFS, OS, independent of clinical-pathologic risk factors (HR 0.16, 95%CI 0.02-0.99, p = 0.05; HR 0.20, 95%CI 0.04-1.07, p = 0.06, respectively). The radiomic index, ENSAT stage, resection status, and Ki67% index incorporated nomogram exhibited better performance for both PFS and OS prediction as compared with the S-GRAS and ENSAT nomogram (C-index: 0.75 vs. C-index: 0.68, p = 0.030 and 0.67, p = 0.025; C-index: 0.78 vs. C-index: 0.72, p = 0.003 and 0.73, p = 0.006). Calibration curve analysis showed that the radiomics-based model performs best in predicting the two-year PFS and the three-year OS. Decision curve analysis demonstrated that the radiomic index nomogram outperformed the S-GRAS and ENSAT nomogram in predicting the two-year PFS and the three-year OS.

CONCLUSION

The contrast CT radiomic-based nomogram performed better than S-GRAS or ENSAT in predicting PFS and OS in ACC patients.

A novel postoperative nomogram and risk classification system for individualized estimation of survival among patients with parotid gland carcinoma after surgery

BACKGROUND

Parotid gland carcinoma (PGC) is a rare but aggressive head and neck cancer, and the prognostic model associated with survival after surgical resection has not yet been established. This study aimed to construct a novel postoperative nomogram and risk classification system for the individualized prediction of overall survival (OS) among patients with resected PGC.

METHODS

Patients with PGC who underwent surgery between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database were randomized into training and validation cohorts (7:3). A nomogram developed using independent prognostic factors based on the results of the multivariate Cox regression analysis. Harrell's concordance index (C-index), time-dependent area under the curve (AUC), and calibration plots were used to validate the performance of the nomogram. Moreover, decision curve analysis (DCA) was performed to compare the clinical use of the nomogram with that of traditional TNM staging.

RESULTS

In this study, 5077 patients who underwent surgery for PGC were included. Age, sex, marital status, tumor grade, histology, TNM stage, surgery type, radiotherapy, and chemotherapy were independent prognostic factors. Based on these independent factors, a postoperative nomogram was developed. The C-index of the proposed nomogram was 0.807 (95% confidence interval 0.797-0.817). Meanwhile, the time-dependent AUC (> 0.8) indicated that the nomogram had a satisfactory discriminative ability. The calibration curves showed good concordance between the predicted and actual probabilities of OS, and DCA curves indicated that the nomogram had a better clinical application value than the traditional TNM staging. Moreover, a risk classification system was built that could perfectly classify patients with PGC into three risk groups.

CONCLUSIONS

This study constructed a novel postoperative nomogram and corresponding risk classification system to predict the OS of patients with PGC after surgery. These tools can be used to stratify patients with high or low risk of mortality and provide high-risk patients with more directed therapies and closer follow-up.

A nomogram risk prediction model for poor outcome of primary brainstem hemorrhage based on clinical data and radiographic features

OBJECTIVE

Primary brainstem hemorrhage (PBSH) is a devastating acute neurological disorder with a poor prognosis. This study aimed to identify risk factors associated with poor outcomes in PBSH patients and develop a novel nomogram for predicting prognosis, with external validation.

METHODS

A total of 379 patients with PBSH were included in the training cohort. The primary outcome of interest was a modified Rankin Scale score (mRS) of 4-6 at 90 days post-onset. Multivariable logistic regression was used to construct a nomogram based on relevant variables. Model performance was tested in the training cohort and externally validated for discriminatory ability, calibration, and clinical utility at a separate institution. The nomogram was also compared to the ICH score in terms of predictive ability.

RESULTS

The poor outcome rate at 90 days was 57.26% (217/379) in the training cohort and 61.27% (106/173) in the validation cohort. Multivariable logistic regression analysis identified age, Glasgow Coma Scale (GCS) score, and hematoma size as significant risk factors for poor outcomes. Nomograms based on these variables demonstrated good discrimination, with an area under the curve (AUC) of 0.855 and 0.836 in the training and validation cohorts, respectively. Furthermore, the nomogram showed superior predictive value to the ICH score for the 90-day outcome in both cohorts.

CONCLUSION

This study developed and externally validated a nomogram risk prediction model for predicting poor outcomes at 90 days in patients with PBSH, using age, GCS score, and hematoma size as predictors. The nomogram demonstrated good discrimination, calibration, and clinical validity, serving as a valuable assessment and decision-making tool.

Development and validation of a nomogram for predicting the risk of vasovagal reactions after plasma donation

BACKGROUND AND OBJECTIVES

Vasovagal reactions (VVRs) are the most common adverse reactions and are frequently associated with serious donor adverse events. Even mild VVRs can lead to a significant reduction in the likelihood of subsequent donations. The purpose of this study is to explore the factors related to the occurrence of VVRs after plasma donation and to construct a nomogram to identify individuals at risk for VVRs to improve the safety of plasma donors.

MATERIALS AND METHODS

We collected the donation data from July 2019 to June 2020 from a plasma center in Sichuan, China, to explore the independent risk factors for vasovagal reactions. From these data, we constructed and validated a predictive model for vasovagal reactions.

RESULTS

VVRs after plasma donation occurred 737 times in 120 448 plasma donations (0.66%). Gender, season, donor status, weight, pulse, duration of donation, and cycle were independent risk factors for VVRs (P< 0.05). The concordance index (C-index) of a logistic model in the derivation cohort was 0.916, with a Hosmer-Lemeshow goodness-of-fit probability of 0.795. The C-index of a logistic model in the validation cohort was 0.916, with a Hosmer-Lemeshow goodness-of-fit probability of 0.224. The calibration curve showed that the predicted results were in good agreement with the actual observed results.

CONCLUSION

This study preliminarily constructed and verified a prediction model for VVRs after plasma donation. The model nomogram is practical and can identify high-risk donors.

A Nomogram for Enhancing the Diagnostic Effectiveness of Solid Breast BI-RADS 3-5 Masses to Determine Malignancy Based on Imaging Aspects of Conventional Ultrasonography and Contrast-Enhanced Ultrasound

BACKGROUND

To establish and validate a nomogram model, which can incorporate clinical data, and imaging features of ultrasound (US) and contrast-enhanced ultrasound (CEUS), for improving the diagnostic efficiency of solid breast lesions.

PATIENTS AND METHODS

A total of 493 patients with solid breast lesions were randomly divided into training (n = 345) and validation (n = 148) cohorts with a ratio of 7:3 and, clinical data and image features of US and CEUS were reviewed and retrospectively analyzed. The breast lesions in both the training and validation cohorts were analyzed using the BI-RADS and nomogram models.

RESULTS

Five variables, including the shape and calcification features of conventional US, enhancement type and size after enhancement features of CEUS, and BI-RADS, were selected to construct the nomogram model. As compared to the BI-RADS model, the nomogram model demonstrated satisfactory discriminative function (area under the receiver operating characteristic [ROC] curves [AUC], 0.940; 95% confidence interval [CI], 0.909 to 0.971; sensitivity, 0.905; and specificity, 0.902 in the training cohort and AUC, 0.968; 95% CI, 0.941 to 0.995; sensitivity, 0.971; and specificity, 0.867 in the validation cohort). In addition, the nomogram model showed good consistency and clinical potential according to the calibration curve and DCA.

CONCLUSION

The nomogram model could identify benign from malignant breast lesions with good performance.

New Findings on Presentation and Outcome of Patients With Adrenocortical Cancer: Results From a National Cohort Study

CONTEXT

Because of the rarity of adrenocortical cancer (ACC), only a few population-based studies are available, and they reported limited details in the characterization of patients and their treatment.

OBJECTIVE

To describe in a nationwide cohort the presentation of patients with ACC, treatment strategies, and potential prognostic factors.

METHODS

Retrospective analysis of 512 patients with ACC, diagnosed in 12 referral centers in Italy from January 1990 to June 2018.

RESULTS

ACC diagnosed as incidentalomas accounted for overall 38.1% of cases, with a frequency that increases with age and with less aggressive pathological features than symptomatic tumors. Women (60.2%) were younger than men and had smaller tumors, which more frequently secreted hormones. Surgery was mainly done with an open approach (72%), and after surgical resection, 62.7% of patients started adjuvant mitotane therapy. Recurrence after tumor resection occurred in 56.2% of patients. In patients with localized disease, cortisol secretion, ENSAT stage III, Ki67%, and Weiss score were associated with an increased risk of recurrence, whereas margin-free resection, open surgery, and adjuvant mitotane treatment were associated with reduced risk. Death occurred in 38.1% of patients and recurrence-free survival (RFS) predicted overall survival (OS). In localized disease, age, cortisol secretion, Ki67%, ENSAT stage III, and recurrence were associated with increased risk of mortality. ACCs presenting as adrenal incidentalomas showed prolonged RFS and OS.

CONCLUSION

Our study shows that ACC is a sex-related disease and demonstrates that an incidental presentation is associated with a better outcome. Given the correlation between RFS and OS, RFS may be used as a surrogate endpoint in clinical studies.

Improved Differential Diagnosis Based on BI-RADS Descriptors and Apparent Diffusion Coefficient for Breast Lesions: A Multiparametric MRI Analysis as Compared to Kaiser Score

RATIONALE AND OBJECTIVES

To develop the nomogram utilizing the American College of Radiology BI-RADS descriptors, clinical features, and apparent diffusion coefficient (ADC) to differentiate benign from malignant breast lesions.

MATERIALS AND METHODS

A total of 341 lesions (161 malignant and 180 benign) were included. Clinical data and imaging features were reviewed. Univariable and multivariable logistic regression analyses were performed to determine the independent variables. ADC as a continuous or classified into binary form with a cutoff value of 1.30 × 10-3 mm2/s, incorporated other independent predictors to construct two nomograms, respectively. Receiver operating curve and calibration plot was employed to test the models' discriminative ability. The diagnostic performance between the developed model and the Kaiser score (KS) was also compared.

RESULTS

In both models, high patient age, the presence of root sign, time-intensity curves (TICs) types (plateau and washout), heterogenous internal enhancement, the presence of peritumoral edema, and ADC were independently associated with malignancy. The AUCs of two multivariable models (AUC, 0.957; 95% CI: 0.929-0.976 and AUC, 0.958; 95% CI: 0.931-0.976) were significantly higher than that of the KS (AUC, 0.919, 95% CI: 0.885-0.946; both P < 0.001). At the same sensitivity of 95.7%, our models showed an increase in specificity by 5.56% (P = 0.076) and 6.11% (P = 0.035), respectively, as compared to the KS.

CONCLUSION

The models incorporating MRI features (root sign, TIC, margins, internal enhancement, and presence of edema), quantitative ADC value, and patient age showed improved diagnostic performance and might have avoided more unnecessary biopsies in comparison with the KS, although further external validation is required.

In-stent restenosis after vertebral artery origin stenosis stenting: a nomogram for risk assessment

OBJECTIVE

To propose a nomogram for individual risk assessment of in-stent restenosis (ISR) after vertebral artery origin stenosis (VAOS) stenting.

METHODS

We included 793 patients with VAOS treated with stenting from October 2006 to May 2013, with a median follow-up of 27.8 months. Cox regression and the least absolute shrinkage and selection operator (LASSO) regression were adopted for variable selection. The nomogram was formulated and validated by concordance indexes (C-indexes) and calibration curves. An in-stent restenosis risk table (ISR-RT) was subsequently generated for risk stratification. Differences between low-, intermediate-, and high-risk levels were shown by Kaplan-Meier curves and compared by log-rank test.

RESULTS

The training and validation set included 594 and 199 patients, with a mean ISR rate of 37.2% and 35.2%, respectively. Stent type (HR=1.64, 95% CI 1.26 to 2.14), stent diameter (HR=2.48, 95% CI 1.77 to 3.48), history of peripheral vascular disease (HR=2.17, 95% CI 1.17 to 4.00), history of transit ischemic attack (HR=1.45, 95% CI 1.05 to 2.14), and left-side involvement (HR=1.33, 95% CI 1.04 to 1.69) were included in the nomogram. The C-indexes at 6 and 12 months were 0.650 and 0.611 in the training set, and 0.713 and 0.603 in the validation set, respectively. Compared with low-risk patients, the intermediate- and high-level group had 1.46 (95% CI 1.05 to 2.04; p=0.0235) and 2.28 (95% CI 1.64 to 3.17; p<0.0001) higher chances of developing ISR in 2 years, respectively.

CONCLUSIONS

A nomogram and a risk evaluation table were developed with good predictive ability for in-stent restenosis among patients with VAOS, which could serve as a practical approach for individualized risk evaluation.

Can a Nomogram Predict Survival After Treatment for an Ankylosing Spondylitis Cervical Fracture in a Patient With Neurologic Impairment? A National, Multicenter Study

BACKGROUND

Ankylosing spondylitis-related cervical spine fracture with neurologic impairment (ASCF-NI) is a rare but often lethal injury. Factors independently associated with survival after treatment remain poorly defined, and identifying patients who are likely to survive the injury remains challenging.

QUESTIONS/PURPOSES

(1) What factors are independently associated with survival after treatment among patients with ASCF-NI? (2) Can a nomogram be developed that is sufficiently simple for clinicians to use that can identify patients who are the most likely to survive after injury?

METHODS

This retrospective study was conducted based on a multi-institutional group of patients admitted and treated at one of 29 tertiary hospitals in China between March 1, 2003, and July 31, 2019. A total of 363 patients with a mean age of 53 ± 12 years were eventually included, 343 of whom were male. According to the National Household Registration Management System, 17% (61 of 363) died within 5 years of injury. Patients were treated using nonsurgical treatment or surgery, including procedures using the anterior approach, posterior approach, or combined anterior and posterior approaches. Indications for surgery included three-column injury, unstable fracture displacement, neurologic impairment or continuous progress, and intervertebral disc incarceration. By contrast, patients generally received nonsurgical treatment when they had a relatively stable fracture or medical conditions that did not tolerate surgery. Demographic, clinical, and treatment data were collected. The primary study goal was to identify which factors are independently associated with death within 5 years of injury, and the secondary goal was the development of a clinically applicable nomogram. We developed a multivariable Cox hazards regression model, and independent risk factors were defined by backward stepwise selection with the Akaike information criterion. We used these factors to create a nomogram using a multivariate Cox proportional hazards regression analysis.

RESULTS

After controlling for potentially confounding variables, we found the following factors were independently associated with a lower likelihood of survival after injury: lower fracture site, more-severe peri-injury complications, poorer American Spinal Injury Association (ASIA) Impairment Scale, and treatment methods. We found that a C5 to C7 or T1 fracture (ref: C1 to C4 and 5; hazard ratio 1.7 [95% confidence interval 0.9 to 3.5]; p = 0.12), moderate peri-injury complications (ref: absence of or mild complications; HR 6.0 [95% CI 2.3 to 16.0]; p < 0.001), severe peri-injury complications (ref: absence of or mild complications; HR 30.0 [95% CI 11.5 to 78.3]; p < 0.001), ASIA Grade A (ref: ASIA Grade D; HR 2.8 [95% CI 1.1 to 7.0]; p = 0.03), anterior approach (ref: nonsurgical treatment; HR 0.5 [95% CI 0.2 to 1.0]; p = 0.04), posterior approach (ref: nonsurgical treatment; HR 0.4 [95% CI 0.2 to 0.8]; p = 0.006), and combined anterior and posterior approach (ref: nonsurgical treatment; HR 0.4 [95% CI 0.2 to 0.9]; p = 0.02) were associated with survival. Based on these factors, a nomogram was developed to predict the survival of patients with ASCF-NI after treatment. Tests revealed that the developed nomogram had good performance (C statistic of 0.91).

CONCLUSION

The nomogram developed in this study will allow us to classify patients with different mortality risk levels into groups. This, coupled with the factors we identified, was independently associated with survival, and can be used to guide more appropriate treatment and care strategies for patients with ASCF-NI.

LEVEL OF EVIDENCE

Level III, therapeutic study.

[Guidelines of the French National ENDOCAN-COMETE, Association of Endocrine Surgery, Society of Urology for the management of adrenocortical carcinoma]

The adrenocortical carcinoma (ACC) is a primary malignant tumor developed from the adrenal cortex, defined by a Weiss score≥3. Its prognosis is poor and depends mainly on the stage of the disease at diagnosis. Care is organized in France by the multidisciplinary expert centers of the national ENDOCAN-COMETE "Adrenal Cancers" network, certified by the National Cancer Institute. This document updates the guidelines for the management of ACC in adults based on the most robust data in the literature. It's divided into 11 chapters: (1) circumstances of discovery; (2) pre-therapeutic assessment; (3) diagnosis of ACC; (4) oncogenetics; (5) prognostic classifications; (6) treatment of hormonal hypersecretion; (7) treatment of localized forms; (8) treatment of relapses; (9) treatment of advanced forms; (10) follow-up; (11) the particular case of ACC and pregnancy. R0 resection of all localized ACC remains an unmet need and it must be performed in expert centers. Flow-charts for the therapeutic management of localized ACC, relapse or advanced ACC are provided. It was written by the experts from the national ENDOCAN-COMETE network and validated by all French Societies involved in the management of these patients (endocrinology, medical oncology, endocrine surgery, urology, pathology, genetics, nuclear medicine, radiology, interventional radiology).

The Enhanced Expression of ZWILCH Predicts Poor Survival of Adrenocortical Carcinoma Patients

Zwilch kinetochore protein (ZWILCH) plays a key role in proper cell proliferation. The upregulation of the ZWILCH gene was observed in many types of cancers, but the association of ZWILCH with adrenocortical carcinoma (ACC) was not investigated so far. The main aim of the presented study was to verify if the enhanced level of the ZWILCH gene can be used as a diagnostic marker for ACC development and progression, as well as a predictor of survival time for ACC patients. The performed analyses included investigation of the ZWILCH expression profile in tumors with publicly available TCGA (The Cancer Genome Atlas) datasets and transcriptomic data from the Gene Expression Omnibus (GEO) database, as well as, in human biological samples of normal adrenal, adrenocortical carcinoma and in commercially available tissue microarrays. The findings demonstrate statistically significant higher ZWILCH gene expression in ACC tissue in comparison with normal adrenal glands. Furthermore, there is a strong correlation between ZWILCH upregulation and tumor mitotic rate and the probability of patient survival. The enhanced ZWILCH level is also connected with the activation of genes involved in cell proliferation and the inhibition of genes related to the immune system. This work contributes to a better understanding of the role of ZWILCH as an ACC biomarker and diagnostic tool.

Prognostic factors and a dynamic model on cancer-specific survival for T1a N0 M0 glottic cancer: A population-based analysis and clinical validation

OBJECTIVES

The survival rate varies tremendously in T_1a N₀ M₀ glottic cancer patients, which may be associated with the difference on patients' characters, such as age, treatment, and marital status. The objective of this study is to identify the vital factors and construct a dynamic prognostic model for predicting the cancer-specific survival (CSS) of patients with T_1a N₀ M₀ glottic cancer.

DESIGN, SETTING, AND PARTICIPANTS

The data of T_1a N₀ M₀ glottic cancer patients were extracted retrospectively from the SEER database between 2004 and 2015, which were randomly divided into the training dataset (70%) and the validation dataset (30%). The training cohort was used to identify independent prognostic factors and build the prognostic nomogram. While the validation cohort was used to validate the applicability of the newly constructed model.

MAIN OUTCOME MEASURES

The model was evaluated with the discrimination, the calibration, and the clinical benefit. The external data collecting from a medical center were used to validate the performance of the prognostic model.

RESULTS

Totally, 3286 eligible patients in the data of the SEER database and 139 eligible patients in our external clinical cohort were finally identified. 5 independent prognostic factors (age, marital status, Grade, primary site surgery, and chemotherapy) were identified and applied to develop the dynamic prognostic tool. C-indexes, receiver operating characteristic curves, calibration curves, and decision curve analyses proved that the prognostic nomogram showed excellent predictive accuracy, ability, and prognostic value. Using internal and external cohorts, the validation of the model also proved its reliability.

CONCLUSION

Prognostic factors for T_1a N₀ M₀ glottic cancer were identified. The novel web-based prognostic prediction tool may be beneficial in clinical decision-making and has value in risk stratification, personalized treatment, and clinical trial design.

Development and Validation of a New Staging System for Esophageal Squamous Cell Carcinoma Patients Based on Combined Pathological TNM, Radiomics, and Proteomics

OBJECTIVE

This study aimed to construct a new staging system for patients with esophageal squamous cell carcinoma (ESCC) based on combined pathological TNM (pTNM) stage, radiomics, and proteomics.

METHODS

This study collected patients with radiomics and pTNM stage (Cohort 1, n = 786), among whom 103 patients also had proteomic data (Cohort 2, n = 103). The Cox regression model with the least absolute shrinkage and selection operator, and the Cox proportional hazards model were used to construct a nomogram and predictive models. Concordance index (C-index) and the integrated area under the time-dependent receiver operating characteristic (ROC) curve (IAUC) were used to evaluate the predictive models. The corresponding staging systems were further assessed using Kaplan-Meier survival curves.

RESULTS

For Cohort 1, the RadpTNM4c staging systems, constructed based on combined pTNM stage and radiomic features, outperformed the pTNM4c stage in both the training dataset 1 (Train1; IAUC 0.711 vs. 0.706, p < 0.001) and the validation dataset 1 (Valid1; IAUC 0.695 vs. 0.659, p < 0.001; C-index 0.703 vs. 0.674, p = 0.029). For Cohort 2, the ProtRadpTNM2c staging system, constructed based on combined pTNM stage, radiomics, and proteomics, outperformed the pTNM2c stage in both the Train2 (IAUC 0.777 vs. 0.610, p < 0.001; C-index 0.898 vs. 0.608, p < 0.001) and Valid2 (IAUC 0.746 vs. 0.608, p < 0.001; C-index 0.889 vs. 0.641, p = 0.009) datasets.

CONCLUSIONS

The ProtRadpTNM2c staging system, based on combined pTNM stage, radiomic, and proteomic features, improves the predictive performance of the classical pTNM staging system.

A novel cuproptosis-related gene model predicts outcomes and treatment responses in pancreatic adenocarcinoma

BACKGROUND

Cuproptosis is recently emerging as a hot spot in cancer research. However, its role in pancreatic adenocarcinoma (PAAD) has not yet been clarified. This study aimed to explore the prognostic and therapeutic implications of cuproptosis-related genes in PAAD.

METHODS

Two hundred thirteen PAAD samples from the International Cancer Genome Consortium (ICGC) were split into training and validation sets in the ratio of 7:3. The Cox regression analyses generated a prognostic model using the ICGC cohort for training (n = 152) and validation (n = 61). The model was externally tested on the Gene Expression Omnibus (GEO) (n = 80) and The Cancer Genome Atlas (TCGA) datasets (n = 176). The clinical characteristics, molecular mechanisms, immune landscape, and treatment responses in model-defined subgroups were explored. The expression of an independent prognostic gene TSC22D2 was confirmed by public databases, real-time quantitative PCR (RT-qPCR), western blot (WB), and immunohistochemistry (IHC).

RESULTS

A prognostic model was established based on three cuproptosis-related genes (TSC22D2, C6orf136, PRKDC). Patients were stratified into high- and low-risk groups using the risk score based on this model. PAAD patients in the high-risk group had a worse prognosis. The risk score was statistically significantly correlated with most clinicopathological characteristics. The risk score based on this model was an independent predictor of overall survival (OS) (HR = 10.7, p < 0.001), and was utilized to create a scoring nomogram with excellent prognostic value. High-risk patients had a higher TP53 mutation rate and a superior response to multiple targeted therapies and chemotherapeutic drugs, but might obtain fewer benefits from immunotherapy. Moreover, elevated TSC22D2 expression was discovered to be an independent prognostic predictor for OS (p < 0.001). Data from public databases and our own experiments showed that TSC22D2 expression was significantly higher in pancreatic cancer tissues/cells compared to normal tissues/cells.

CONCLUSION

This novel model based on cuproptosis-related genes provided a robust biomarker for predicting the prognosis and treatment responses of PAAD. The potential roles and underlying mechanisms of TSC22D2 in PAAD need further explored.

Development of a nomogram for predicting 90-day mortality in patients with sepsis-associated liver injury

The high mortality rate in sepsis patients is related to sepsis-associated liver injury (SALI). We sought to develop an accurate forecasting nomogram to estimate individual 90-day mortality in SALI patients. Data from 34,329 patients were extracted from the public Medical Information Mart for Intensive Care (MIMIC-IV) database. SALI was defined by total bilirubin (TBIL) > 2 mg/dL and the occurrence of an international normalized ratio (INR) > 1.5 in the presence of sepsis. Logistic regression analysis was performed to establish a prediction model called the nomogram based on the training set (n = 727), which was subsequently subjected to internal validation. Multivariate logistic regression analysis showed that SALI was an independent risk factor for mortality in patients with sepsis. The Kaplan‒Meier curves for 90-day survival were different between the SALI and non-SALI groups after propensity score matching (PSM) (log rank: P < 0.001 versus P = 0.038), regardless of PSM balance. The nomogram demonstrated better discrimination than the sequential organ failure assessment (SOFA) score, logistic organ dysfunction system (LODS) score, simplified acute physiology II (SAPS II) score, and Albumin-Bilirubin (ALBI) score in the training and validation sets, with areas under the receiver operating characteristic curve (AUROC) of 0.778 (95% CI 0.730-0.799, P < 0.001) and 0.804 (95% CI 0.713-0.820, P < 0.001), respectively. The calibration plot showed that the nomogram was sufficiently successful to predict the probability of 90-day mortality in both groups. The DCA of the nomogram demonstrated a higher net benefit regarding clinical usefulness than SOFA, LODS, SAPSII, and ALBI scores in the two groups. The nomogram performs exceptionally well in predicting the 90-day mortality rate in SALI patients, which can be used to assess the prognosis of patients with SALI and may assist in guiding clinical practice to enhance patient outcomes.

Treatment outcomes of adjuvant radiotherapy in adrenocortical carcinoma - A 13-years experience from a tertiary care centre

Purpose

Adrenocortical carcinoma (ACC) is a rare and highly aggressive malignant neoplasm, usually diagnosed in advanced stage. Role and efficacy of adjuvant radiotherapy has not been well defined. The objective of this study is to describe the various clinical characteristics and prognostic factors affecting the survival of ACC along with the role radiotherapy on overall survival and relapse free survival.

Methods

A retrospective analysis of 30 patients registered between 2007 and 2019 was carried out. The medical records containing clinical and treatment details were analysed. Data was analysed using SPSS 25.0. Survival curves were computed using Kaplan-Meier method. Univariate and multivariate analyses were performed to analyze the prognostic factors affecting the outcome. A p value of less than 0.05 was considered to be statistically significant.

Results

The median age of patients was 37.5 years (range, 5-72 years). 20 patients were females. Twenty-six patients had advanced stage (III/IV) disease while only four patients presented in early stage. Twenty-six patients underwent total adrenalectomy. Eighty three percent patients received adjuvant radiation therapy. The median follow up was 35.5 months (range, 7 monthss-132months). The estimated three- and 5-years overall survival (OS) was 67.2% and 23.3%, respectively. Capsular invasion and positive margins were the independent prognostic factors influencing both OS and relapse free survival (RFS). Out of 25 patients who received adjuvant radiation, only three patients had local relapse.

Conclusion

ACC is a rare and aggressive neoplasm with majority of patients presenting in advanced stage. Surgical resection with negative margins remains the mainstay of treatment. Capsular invasion and positive margins are independent prognostic factors for survival. Adjuvant radiation reduces the risk of local relapse and is well tolerated. Radiation can be used effectively in adjuvant and palliative settings in ACC.

A 6-month prognostic nomogram incorporating hemoglobin level for intracerebral hemorrhage in younger adults

OBJECTIVE

Intracerebral hemorrhage (ICH) is the second most common subtype of stroke, with high mortality and morbidity. At present, there are no effective 6-month prognostic markers, particularly for younger patients. The aim of this research was to construct a new valuable prognostic nomogram model incorporating haemoglobin levels for adult patients with ICH.

METHODS

Patients aged between 18 and 50 presenting with intracerebral haemorrhage at the Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology between January 1st 2012 and December 31st 2018 were included in this retrospective study. Independent factors of prognosis were identified by univariate and multivariate logistic regression analyses, and a new nomogram model was constructed and validated. The clinical value of the nomogram model was subsequently explored utilizing decision curve analysis and clinical impact curves.

RESULTS

In total, 565 patients were enrolled in this study, 117 (20.7%) of whom developed an unfavourable prognosis. Infratentorial lesion (adjusted odds ratio [aOR] = 3.708, 95% confidence interval [CI], 1.490-9.227; P = 0.005) was the most significant unfavourable outcome. Age ([aOR] = 1.054; 95% CI, 1.014-1.096; P = 0.008), hematoma volume (aOR = 1.014, 95% CI, 1.002-1.027; P = 0.024), haemoglobin (aOR = 0.981, 95% CI, 0.969-0.993; P = 0.002), blood glucose (aOR = 1.135, 95% CI, 1.037-1.241; P = 0.005) and NIHSS (aOR = 1.105, 95% CI, 1.069-1.141; P < 0.001) were independent risk factors. Based on these 6 factors, the nomogram can be employed to predict early functional prognosis with high accuracy (AUC 0.791). Decision curve analysis and clinical impact curves showed an increased net benefit for utilizing the nomogram.

CONCLUSION

The haemoglobin level at admission may be an easily overlooked factor in clinical work. This new nomogram model could be a promising and convenient tool to predict the early functional prognosis of adults with ICH. More prospective multicentre studies are needed to validate these findings.

Nomogram for predicting the distal adding-on phenomenon in severe and rigid scoliosis

Background

The distal adding-on phenomenon has attracted extensive discussion in the field of spine surgery due to the continual occurrence after scoliosis correction. Previous work has mainly focused on adolescent idiopathic scoliosis (AIS), and a relatively high number of theories for the mechanism of the distal adding-on phenomenon has been proposed for these kinds of patients. Severe and rigid scoliosis, as a special disease form, has a unique etiology, clinical manifestations and internal mechanisms distinct from those of AIS. Given the uniqueness of this disease, the mechanism and causes of the distal adding-on phenomenon have been infrequently studied in depth.

Objective

To define clinical and radiological factors associated with distal adding-on in patients with severe and rigid scoliosis.

Methods

Radiographic parameters and demographic data of patients with severe and rigid scoliosis were evaluated preoperatively, after posterior instrumentation and fusion surgery, and at the final follow-up via radiographs. According to the appearance of distal adding-on at the final follow-up, the patients were grouped into the Adding-on and the Non-adding-on groups. Various radiological parameters were analyzed in stepwise multivariate logistic regression to identify the variables associated with distal adding-on, which were then incorporated into a nomogram. The predictive performance and calibration of the nomograms for distal adding-on were assessed using C statistics and calibration plots.

Results

93 patients (21 in the Adding-on and 72 in the Non-adding-on group) were included. The incidence of distal adding-on was 22.6%. The variables associated with distal adding-on were the anterior release, posterior internal distraction, and later posterior spinal fusion (IP) procedure, the posterior vertebral column resection and posterior spinal fusion (PVCR) procedure, postoperative apical vertebral translation (Post-AVT) and preoperative slope of the line linking the pedicles on the concave side of the upper- and lower-end vertebrae (Tan α). Combining these factors, the nomogram achieved a concordance index of 0.92 in predicting distal adding-on and had well-fitted calibration curves.

Conclusions

For patient with a negative Tanα in severe and rigid scoliosis, the risk of distal adding-on tended to increase, and it is recommended to give priority to IP or PVCR. In the final correction, a smaller Post-AVT should not be pursued excessively.

Prognostic predictors of adrenocortical carcinoma: A single-center thirty-year experience

BACKGROUND

The prognosis of adrenocortical carcinoma (ACC) is poor but highly variable. The present study aimed to characterize patients with ACC at a single center in Taiwan and to determine the prognostic predictors of overall and progression-free survival.

METHODS

Medical records of patients, who were diagnosed with ACC at Taipei Veterans General Hospital between January 1992 and June 2021, were reviewed. Patient demographics, tumor characteristics, and subsequent treatment were analyzed with regard to overall survival and progression-free survival using Kaplan-Meier methods and a Cox regression model.

RESULTS

Sixty-seven patients were included. Females (65.7%) were more susceptible to ACC, with a younger onset and active hormonal secretion. One-half of the patients exhibited distant metastases at the time of diagnosis. The European Network for the Study of Adrenal Tumours (ENSAT) stage (hazard ratio [HR] 3.60 [95% confidence interval (CI) 1.25-10.38]; p=0.018), large vessel invasion (HR 5.19 [95% CI 1.75-15.37]; p=0.003), and mitotane use (HR 0.27 [95% CI 0.11-0.70]; p=0.007) were significantly associated with overall survival (OS). There was no single factor independently associated with progression-free survival.

CONCLUSION

ENSAT stage had a substantial impact on overall survival though there was no difference in OS between patients with stage II and stage III ACC. Large vessel invasion portended poor prognosis and influenced OS significantly. Moreover, mitotane only improved clinical outcomes of patients with stage IV disease.

Treatment of adrenocortical carcinoma: oncological and endocrine outcomes

PURPOSE OF REVIEW

Adrenocortical carcinoma (ACC) is a rare, aggressive disease with a paucity of data and great variability between published studies regarding its treatment. This review provides information on current clinical management and oncological and endocrine outcomes.

RECENT FINDINGS

Complete surgical resection is the only potentially curative treatment for adrenocortical carcinoma (ACC). Adjuvant mitotane treatment is recommended in patients with favourable/intermediate prognosis. As part of the endocrine follow-up, steroid hormones and thyroid hormones may be decreased or increased and may need to be substituted or suppressed. Recurrences are common. If the disease-free interval is more than 12 months, surgery is a treatment if complete resection is feasible. In advanced/metastatic ACC patients, the prognosis is poor. Mitotane monotherapy is only appropriate for patients with low tumour burden and indolent disease. Patients with unfavourable prognosis should be treated with aggressive cytotoxic therapy. Patients requiring third-line treatment should be considered for clinical trials. Immunotherapy and targeted therapy are currently being investigated, but have so far yielded only unsatisfactory results.

SUMMARY

There is scarce evidence for the treatment of ACC, which often complicates clinical decision-making. Patients who progress on EDP-M should be treated in clinical trials.

Development and validation of a nomogram predicting one-year mortality in patients undergoing percutaneous coronary intervention

OBJECTIVE

To formulate a nomogram to predict the risk of one-year mortality after percutaneous coronary intervention (PCI) based on a large-scale real-world Asian cohort.

METHODS

This study cohort included consecutive patients undergoing PCI in the National Center for Cardiovascular Diseases of China. The endpoint was all-cause mortality. Least absolute shrinkage and selection operator Cox regression and backward stepwise regression were used to select potential risk factors. A nomogram based on the predictors was accordingly constructed to predict one-year mortality. The performance of the nomogram was evaluated. Patients were stratified into low-, intermediate- and high-risk groups according to the tertile points in the nomogram and compared by the Kaplan-Meier analysis.

RESULTS

A total of 9603 individuals were included in this study and randomly divided into the derivation cohort (60%) and the validation cohort (40%). Six variables were selected to formulate the nomogram, including age, renal insufficiency, cardiac dysfunction, previous cerebrovascular disease, previous PCI, and TIMI 0-1 before PCI. The area under the curve of this nomogram regarding one-year mortality risks were 0.792 and 0.754 in the derivation cohort and validation cohort, respectively. Kaplan-Meier curve successfully stratified the patients according to three risk groups. This nomogram calibrated well and exhibited satisfactory clinical utility in the decision curve analysis.

CONCLUSIONS

This study developed and validated a simple-to-use nomogram predicting one-year mortality risk in Asian patients undergoing PCI and could help clinicians make risk-dependent decisions.

Nomogram to predict overall survival in patients with primary bladder neuroendocrine carcinoma: a population-based study

Aim: To develop a prognostic model to predict the overall survival of primary bladder neuroendocrine carcinoma (BNEC) patients. Methods: Using univariate and multivariate Cox regression analyses, a nomogram was constructed. Calibration curves, receiver operating characteristic curves and C-index were utilized to evaluate the performance. Results: The study enrolled 906 BNEC patients. The following variables were incorporated in the nomogram: age, marital status, Tumor node metastasis (TNM) stage, chemotherapy and surgery. The nomogram had a C-index of 0.702 in the training cohort and 0.724 in the validation cohort. Conclusion: Compared with the TNM staging system, the proposed nomogram exhibits superior prognostic discrimination and survival prediction.

Construction and validation of a prognostic model for predicting overall survival of primary adrenal malignant tumor patients: A population-based study with 1,080 patients

Objective

Primary adrenal malignant tumor is rare. The factors affecting the prognosis remain poorly defined. This study targeted to construct and corroborate a model for predicting the overall survival of adrenal malignant tumor patients.

Methods

We investigated the SEER database for patients with primary adrenal malignant tumor. 1,080 patients were divided into a construction cohort (n = 756) and a validation cohort (n = 324), randomly. The prognostic factors for overall survival were evaluated using univariate and multivariate Cox analyses. The nomogram was constructed and then validated with C-index, calibration curve, time-dependent ROC curve, and decision curve analysis in both cohorts. Then we divided the patients into 3 different risk groups according to the total points of the nomogram and analyzed their survival status by Kaplan-Meier curve with log-rank test.

Results

The baseline characteristics of these two cohorts were not statistically different (P > 0.05). Using univariate and multivariate Cox analyses, 5 variables, including age, tumor size, histological type, tumor stage, and surgery of primary site, were distinguished as prognostic factors (P < 0.05). Based on these variables, we constructed a nomogram to predict the 3- year, 5- year, and 10-year overall survival. The C-indexes were 0.780 (0.760–0.800) in the construction cohort and 0.780 (0.751–0.809) in the validation cohort. In both cohorts, the AUC reached a fairly high level at all time points. The internal and external calibration curves and ROC analysis showed outstanding accuracy and discrimination. The decision curves indicated excellent clinical usefulness. The best cut-off values for the total points of the nomogram were 165.4 and 243.1, and the prognosis was significantly different for the three different risk groups (P < 0.001).

Conclusion

We successfully constructed a model to predict the overall survival of primary adrenal malignant tumor patients. This model was validated to perform brilliantly internally and externally, which can assist us in individualized clinical management.

Development and validation of a nomogram for decannulation in patients with neurological injury: A prognostic accuracy study

BACKGROUND

Tracheostomy is a lifesaving procedure provided for patients with severe neurological injury. However, there is a lack of clarity about whether patients can be decannulated within 6 months in those receiving tracheostomy and what factors can be detected as a predictor for decannulation.

OBJECTIVE

The objective of this study was to explore predictive factors of decannulation in patients with neurological injury receiving tracheostomy within 6 months and construct a novel nomogram model for clinical diagnosis and treatment.

METHODS

This retrospective observational study enrolled patients with neurological injury who were admitted to the ICU of neurosurgical department in the First Affiliated Hospital of Nanjing Medical University between January 2016 and March 2021. Patients were divided into decannulation group and cannulation group according to whether tracheostomy tube removal was performed within 6 months after tracheostomy. Multivariable logistic regression analysis was performed to determine associated risk factors with a bootstrap backward selection process. The nomogram to assess the probability of decannulation at 6 months was constructed based on the regression coefficients of the associated factors and validated by bootstrap resampling. Model performance was measured by examining discrimination (Harrell's C-index), calibration (calibration plots), and utility (Kaplan-Meier curves stratified by the tertile of the predicted probability calculated and subgroup analysis stratified by age and intervention).

RESULTS

A total of 40.1% (147/367) of patients decannulated within 6 months. Significant variables in multivariable logistic regression analysis were age (odds ratio [OR], 0.972; 95% confidence interval [CI], 0.954-0.990), National Institutes of Health Stroke Scale (NIHSS) score (OR, 0.936; 95% CI, 0.911-0.963), early rehabilitation (OR, 5.062; 95% CI, 2.889-8.868), shock (OR, 0.175; 95% CI, 0.058-0.533), and secondary surgery (OR, 0.210; 95% CI, 0.078-0.566). The area under receiver operating characteristic curve estimated with these variables was of 0.793 (95% CI, 0.747-0.838; P < 0.001). A nomogram prediction model was constructed to predict the probability of decannulation in tracheostomized patients with a concordance index of 0.788 after internal validation.

CONCLUSION

We developed a nomogram that can predict the probability of decannulation within 6 months in tracheostomized neurological injury patients. The nomogram, including age, NIHSS scores, early rehabilitation, shock, and secondary surgery, may assist clinicians in estimating patients' prognosis.

A risk score model of contrast-induced acute kidney injury in patients with emergency percutaneous coronary interventions

Background

The previously built score models of contrast-induced acute kidney injury (CI-AKI) were principally founded on selective percutaneous coronary intervention (PCI) cases. Our study was to form a risk score model of CI-AKI and make a temporal validation in a population who underwent emergency PCIs.

Methods

We included patients who underwent emergency PCIs from 2013 to 2018 and divided them into the derivation and validation cohorts. Logistic regression analysis was harnessed to create the risk model. In this research, we defined CI-AKI as an increase in serum creatinine (SCr) ≥0.5 mg/dL (44.2 μmol/L) above baseline within seven days following exposure to contrast medium.

Results

A total of 3564 patients who underwent emergency PCIs were enrolled and divided into the derivation (2376 cases) and validation cohorts (1188 cases), with CI-AKI incidence of 6.61 and 5.39%, respectively. By logistic analysis, the CI-AKI risk score model was constituted by 8 variables: female (1 point), history of transient ischemic attack (TIA)/stroke (1 point), left ventricular ejection fraction (LVEF) classification (1 point per class), big endothelin-1 (ET-1) classification (1 point per class), estimated glomerular filtration rate (eGFR) classification (1 point per class), intra-aortic balloon pump (IABP) application (1 point), left anterior descending (LAD) stented (1 point), and administration of diuretic (2 points). The patients could be further divided into three groups: low-risk, moderate-risk, and high-risk groups, in accordance with the risk scores of 3–6, 7–10, and ≥11 points, and to the CI-AKI rates of 1.4, 11.9, and 42.6%. The CI-AKI risk score model performed well in discrimination (C statistic = 0.787, 95% CI: 0.731–0.844) and calibration ability, and showed a superior clinical utility.

Conclusion

We developed a simple CI-AKI risk score model which performs well as a tool for CI-AKI prediction in patients who underwent emergency PCIs.

ENDOCRINE TUMOURS: Our experience with the management of patients with non-metastatic adrenocortical carcinoma

Adrenocortical carcinoma (ACC) accounts for a minority of all malignant tumors in adults. Surgery remains the most important therapeutic option for non-metastatic ACC. Whether a subset of patients with small ACC may benefit from minimally invasive surgery remains a debated issue, but we believe that surgeon's expertise is more important than surgical technique to determine outcome. However, even a state-of-the-art surgery cannot prevent disease recurrence that is determined mainly by specific tumor characteristics. We consider that the concomitant presence of the following features characterizes a cohort of patients at low risk of recurrence, (i) R0 resection (microscopically free margin), (ii) localized disease (stage I-II ACC), and (iii) low-grade tumor (ki-67 <10%). After the ADIUVO study, we do not recommend adjuvant mitotane as a routine measure for such patients, who can be managed with active surveillance thus sparing a toxic treatment. Patients at average risk of recurrence should be treated with adjuvant mitotane. For patients at very high risk of recurrence, defined as the presence of at least one of the following: Ki67 >30%, large venous tumor thrombus, R1 resection or stage IV ACC, we increasingly recommend to combine mitotane with four cycles of platinum-based chemotherapy. However, patients at moderate-to-high risk of recurrence should be ideally enrolled in the ongoing ADIUVO2 trial. We do not use adjuvant radiotherapy of the tumor bed frequently at our institutions, and we select patients with incomplete resection, either microscopically or macroscopically, for this treatment. In the long-term, prospective multicenter trials are required to improve patient care.

ANAID-ICH nomogram for predicting unfavorable outcome after intracerebral hemorrhage

OBJECTIVE

Diffusion-weighted imaging lesions (DWILs) are associated with unfavorable outcome in intracerebral hemorrhage (ICH). We proposed a novel predictive nomogram incorporating DWILs.

METHODS

A total of 738 patients with primary ICH in a tertiary hospital were prospectively enrolled as a training cohort. DWILs were defined as remote focal hyperintensities on DWI corresponding to low intensities on apparent diffusion coefficient images and remote from the focal hematoma. The outcome of interest was modified Rankin Scale scores of 4-6 at 90 days after onset. Multivariate logistic regression was used to construct a nomogram. Model performance was tested in the training cohort and externally validated with respect to discrimination, calibration, and clinical usefulness in another institute. Additionally, the nomogram was compared with the ICH score in terms of predictive ability.

RESULTS

Overall, 153 (20.73%) and 23 (15.54%) patients developed an unfavorable outcome in the training and validation cohorts, respectively. The multivariate analysis revealed that age, National Institutes of Health Stroke Scale (NIHSS) score, anemia, infratentorial location, presence of DWILs, and prior ICH were associated with unfavorable outcome. Our ANAID-ICH nomogram was constructed according to the aforementioned variables; the area under the receiver operating characteristic curve was 0.842 and 0.831 in the training and validation sets, respectively. With regard to the 90-day outcome, the nomogram showed a significantly higher predictive value than the ICH score in both cohorts.

CONCLUSIONS

The ANAID-ICH nomogram comprising age, NIHSS score, anemia, infratentorial location, presence of DWILs, and prior ICH may facilitate the identification of patients at higher risk for an unfavorable outcome.

A nomogram predicting 30-day mortality in patients undergoing percutaneous coronary intervention

Background and aims

Early detection of mortality after percutaneous coronary intervention (PCI) is crucial, whereas most risk prediction models are based on outdated cohorts before the year 2000. This study aimed to establish a nomogram predicting 30-day mortality after PCI.

Materials and methods

In total, 10,444 patients undergoing PCI in National Center for Cardiovascular Diseases in China were enrolled to establish a nomogram to predict 30-day mortality after PCI. The nomogram was generated by incorporating parameters selected by logistic regression with the stepwise backward method.

Results

Five features were selected to build the nomogram, including age, male sex, cardiac dysfunction, STEMI, and TIMI 0–2 after PCI. The performance of the nomogram was evaluated, and the area under the curves (AUC) was 0.881 (95% CI: 0.8–0.961). Our nomogram exhibited better performance than a previous risk model (AUC = 0.7, 95% CI: 0.586–0.813) established by Brener et al. The survival curve successfully stratified the patients above and below the median score of 4.

Conclusion

A novel nomogram for predicting 30-day mortality was established in unselected patients undergoing PCI, which may help risk stratification in clinical practice.

Cytoreductive Surgery of the Primary Tumor in Metastatic Adrenocortical Carcinoma: Impact on Patients' Survival

CONTEXT

The role of cytoreduction of adrenocortical carcinoma (ACC) remains poorly understood.

OBJECTIVE

To analyze the impact of cytoreductive surgery of the primary tumor in patients with metastatic ACC.

DESIGN AND SETTING

We performed a multicentric, retrospective paired cohort study comparing the overall survival (OS) in patients with metastatic ACC who were treated either with cytoreductive surgery (CR group) or without cytoreductive surgery (no-CR group) of the primary tumor. Data were retrieved from 9 referral centers in the American-Australian-Asian Adrenal Alliance collaborative research group.

PATIENTS

Patients aged ≥18 years with metastatic ACC at initial presentation who were treated between January 1, 1995, and May 31, 2019.

INTERVENTION

Performance (or not) of cytoreductive surgery of the primary tumor.

MAIN OUTCOME AND MEASURES

A propensity score match was done using age and the number of organs with metastasis (≤2 or >2). The main outcome was OS, determined from the date of diagnosis until death or until last follow-up for living patients.

RESULTS

Of 339 patients pooled, 239 were paired and included: 128 in the CR group and 111 in the no-CR group. The mean follow-up was 67 months. Patients in the no-CR group had greater risk of death than did patients in the CR group (hazard ratio [HR] = 3.18; 95% CI, 2.34-4.32). Independent predictors of survival included age (HR = 1.02; 95% CI, 1.00-1.03), hormone excess (HR = 2.56; 95% CI, 1.66-3.92), and local metastasis therapy (HR = 0.41; 95% CI, 0.47-0.65).

CONCLUSION

Cytoreductive surgery of the primary tumor in patients with metastatic ACC is associated with prolonged survival.

S-GRAS score for prognostic classification of adrenocortical carcinoma: an international, multicenter ENSAT study

OBJECTIVE

Adrenocortical carcinoma (ACC) has an aggressive but variable clinical course. Prognostic stratification based on the European Network for the Study of Adrenal Tumours stage and Ki67 index is limited. We aimed to demonstrate the prognostic role of a points-based score (S-GRAS) in a large cohort of patients with ACC.

DESIGN

This is a multicentre, retrospective study on ACC patients who underwent adrenalectomy.

METHODS

The S-GRAS score was calculated as a sum of the following points: tumour stage (1-2 = 0; 3 = 1; 4 = 2), grade (Ki67 index 0-9% = 0; 10-19% = 1; ≥20% = 2 points), resection status (R0 = 0; RX = 1; R1 = 2; R2 = 3), age (<50 years = 0; ≥50 years = 1), symptoms (no = 0; yes = 1), and categorised, generating four groups (0-1, 2-3, 4-5, and 6-9). Endpoints were progression-free survival (PFS) and disease-specific survival (DSS). The discriminative performance of S-GRAS and its components was tested by Harrell's Concordance index (C-index) and Royston-Sauerbrei's R2D statistic.

RESULTS

We included 942 ACC patients. The S-GRAS score showed superior prognostic performance for both PFS and DSS, with best discrimination obtained using the individual scores (0-9) (C-index = 0.73, R2D = 0.30, and C-index = 0.79, R2D = 0.45, respectively, all P < 0.01vs each component). The superiority of S-GRAS score remained when comparing patients treated or not with adjuvant mitotane (n = 481 vs 314). In particular, the risk of recurrence was significantly reduced as a result of adjuvant mitotane only in patients with S-GRAS 4-5.

CONCLUSION

The prognostic performance of S-GRAS is superior to tumour stage and Ki67 in operated ACC patients, independently from adjuvant mitotane. S-GRAS score provides a new important guide for personalised management of ACC (i.e. radiological surveillance and adjuvant treatment).

Computer-assisted quantification of tumor-associated collagen signatures to improve the prognosis prediction of breast cancer

BACKGROUND

Collagen fibers play an important role in tumor initiation, progression, and invasion. Our previous research has already shown that large-scale tumor-associated collagen signatures (TACS) are powerful prognostic biomarkers independent of clinicopathological factors in invasive breast cancer. However, they are observed on a macroscale and are more suitable for identifying high-risk patients. It is necessary to investigate the effect of the corresponding microscopic features of TACS so as to more accurately and comprehensively predict the prognosis of breast cancer patients.

METHODS

In this retrospective and multicenter study, we included 942 invasive breast cancer patients in both a training cohort (n = 355) and an internal validation cohort (n = 334) from one clinical center and in an external validation cohort (n = 253) from a different clinical center. TACS corresponding microscopic features (TCMFs) were firstly extracted from multiphoton images for each patient, and then least absolute shrinkage and selection operator (LASSO) regression was applied to select the most robust features to build a TCMF-score. Finally, the Cox proportional hazard regression analysis was used to evaluate the association of TCMF-score with disease-free survival (DFS).

RESULTS

TCMF-score is significantly associated with DFS in univariate Cox proportional hazard regression analysis. After adjusting for clinical variables by multivariate Cox regression analysis, the TCMF-score remains an independent prognostic indicator. Remarkably, the TCMF model performs better than the clinical (CLI) model in the three cohorts and is particularly outstanding in the ER-positive and lower-risk subgroups. By contrast, the TACS model is more suitable for the ER-negative and higher-risk subgroups. When the TACS and TCMF are combined, they could complement each other and perform well in all patients. As expected, the full model (CLI+TCMF+TACS) achieves the best performance (AUC 0.905, [0.873-0.938]; 0.896, [0.860-0.931]; 0.882, [0.840-0.925] in the three cohorts).

CONCLUSION

These results demonstrate that the TCMF-score is an independent prognostic factor for breast cancer, and the increased prognostic performance (TCMF+TACS-score) may help us develop more appropriate treatment protocols.

Nomogram to predict survival of patients with advanced and metastatic pancreatic Cancer

BACKGROUND

Nomograms are rarely employed to estimate the survival of patients with advanced and metastatic pancreatic cancer (PC). Herein, we developed a comprehensive approach to using a nomogram to predict survival probability in patients with advanced and metastatic PC.

METHODS

A total of 323 patients with advanced and metastatic PC were identified from the Chinese People's Liberation Army (PLA) General Hospital. A baseline nomogram was constructed using baseline variables of 323 patients. Additionally, 233 patients, whose tumors showed initial responses to first-line chemotherapy, were enrolled in the chemotherapy response-based model. 128 patients and 108 patients with advanced and metastatic PC from January 2019 to April 2021 were selected for external validating baseline model and chemotherapy response-based model. The 1-year and 2-year survival probability was evaluated using multivariate COX regression models. The discrimination and calibration capacity of the nomograms were assessed using C-statistic and calibration plots. The predictive accuracy and net benefit of the nomograms were evaluated using ROC curve and DCA, respectively.

RESULTS

In the baseline model, six variables (gender, KPS, baseline TB, baseline N, baseline WBC and baseline CA19-9) were used in the final model. In the chemotherapy response-based model, nine variables (KPS, gender, ascites, baseline N, baseline CA 19-9, baseline CEA, change in CA 19-9 level at week, change in CEA level at week and initial response to chemotherapy) were included in the final model. The C-statistics of the baseline nomogram and the chemotherapy response-based nomogram were 0.67 (95% CI, 0.62-0.71) and 0.74 (95% CI, 0.69-0.77), respectively.

CONCLUSION

These nomograms were constructed to predict the survival probability of patients of advanced and metastatic PC. The baseline model and chemotherapy response-based model performed well in survival prediction.

Combination of Mitotane and Locoregional Treatments in Low-volume Metastatic Adrenocortical Carcinoma

CONTEXT

European and French guidelines for ENSAT stage IV low tumor burden or indolent adrenocortical carcinoma (ACC) recommend a combination of mitotane and locoregional treatments (LRT) as first-line treatment. Nevertheless, the benefit of LRT in combination with mitotane has never been evaluated in this selected group of patients.

OBJECTIVE

This work aimed to evaluate the therapeutic strategy of LRT combined with mitotane in patients with low tumor burden stage IVA ACC.

METHODS

A retrospective chart review was performed from 2003 to 2018 of patients with stage IV ACC with 2 or fewer tumoral organs who received mitotane in our center. The primary end point was the delay between mitotane initiation and first systemic chemotherapy. Secondary end points were progression-free survival (PFS) and overall survival (OS) from mitotane initiation. Adjusted analyses were performed on the main prognostic factors.

RESULTS

Out of 79 included patients, 48 (61%) patients were female and the median age at stage IVA diagnosis was 49.8 years (interquartile range [IQR], 38.8-60.0 years). Metastatic sites were mainly lungs (76%) and liver (48%). Fifty-eight (73%) patients received LRT including adrenal bed radiotherapy (14 patients, 18%), surgery (37 patients, 47%), and/or interventional radiology (35 patients, 44%). Median time between mitotane initiation and first chemotherapy administration was 9 months (IQR, 4-18 months). Median PFS1 (first tumor-progression) was 6.0 months (95% CI, 4.5-8.6). Median OS was 46 months (95% CI, 41-68). PFS1, PFS2, and OS were statistically longer in the mitotane plus LRT group compared to the mitotane-only group (hazard ratio [HR] = 0.39; 95% CI, 0.22-0.68; HR = 0.35; 95% CI, 0.20-0.63; and HR = 0.27; 95% CI, 0.14-0.50, respectively). Ten (13%) patients achieved complete response (CR), all from the mitotane plus LRT group.

CONCLUSION

Our results endorse European and French guidelines for stage IV ACC with 2 or fewer tumor organs and favor the combination of mitotane and LRT as first-line treatment. For the first time, a significant number of CRs were observed. Prospective studies are expected to confirm these findings.

Nomogram to predict overall survival of patients with pseudomyxoma peritonei of appendiceal origin: A retrospective cohort study

BACKGROUND

Pseudomyxoma peritonei (PMP) is a rare disease, with the rate of overall survival (OS) influenced by many factors. The present study aimed to define independent predictors and establish a nomogram for individual risk prediction in PMP patients.

METHODS

One hundred forty-seven PMP patients were consecutively included between June 1, 2013, and November 22, 2019. The log-rank test was used to compare the OS rate between groups; subsequently, variables with p < .10 were subjected to multivariate Cox modeling for defining independent prediction indicators. Finally, a nomogram was established based on independent prognosticators and assessed for internal validation.

RESULTS

Multivariate Cox analysis showed that D-dimer level, carbohydrate antigen (CA) 125 level, CA 19-9 level, degree of radical surgery, and histological grade were all independently associated with OS in PMP patients. A nomogram was plotted and underwent internal validation. The discrimination ability of the nomogram revealed a good predictive ability as indicated by the C-index value (0.825), and calibration plots confirmed good consistency between the predicted and observed survival probabilities.

CONCLUSIONS

Five independent prognostic factors for predicting the survival of PMP patients were identified, and the nomogram based on these independent indicators showed a reasonable discrimination ability for individual risk prediction.

Ultrasound-Based Nomogram for Distinguishing Malignant Tumors from Nodular Sclerosing Adenoses in Solid Breast Lesions

OBJECTIVES

Nodular sclerosing adenoses (NSAs) and malignant tumors (MTs) may coexist and are often classified into the same Breast Imaging Reporting and Data System (BI-RADS) category. We aimed to build and validate an ultrasound-based nomogram to distinguish MT from NSA for building a precise sequence of biopsies.

MATERIALS AND METHODS

The training cohort included 156 patients (156 masses) with NSA or MT at one study institution. We used best subset regression to determine the predictors for building a nomogram from ultrasonic characteristics and patients' age. Model performance and clinical utility were evaluated using Brier score, concordance (C)-index, calibration curve, and decision curve analysis. The independent validation cohort consisted of 162 patients (162 masses) from a separate institution.

RESULTS

Through best subset regression, we selected 6 predictors to develop nomogram: age, calcification, echogenic rim, vascularity distribution, tumor size, and thickness of breast parenchyma. Brier score and C-index of the nomogram in the training cohort were 0.068 and 0.967 (95% confidence interval [CI]: 0.941-0.993), respectively. In addition, calibration curve demonstrated good agreement between prediction and pathological result. In the validation cohort, the nomogram still obtained a favorable C-index score of 0.951 (95% CI: 0.919-0.983) and fine calibration. Decision curve analysis showed that the model was clinically useful.

CONCLUSIONS

If multiple NSA and MT masses are present in the same patient and are classified into the same BI-RADS category, our nomogram can be used as a supplement to the BI-RADS category for accurate biopsy of the mass most likely to be MT.

Clinical management and outcomes associated with etoposide, doxorubicin, and cisplatin plus mitotane treatment in metastatic adrenocortical carcinoma: a single institute experience

BACKGROUND

Adrenocortical carcinoma (ACC) is a rare and aggressive disease that is often diagnosed at an advanced stage. There is no standard treatment for metastatic ACC; EDP-M (etoposide, doxorubicin, and cisplatin plus mitotane) is one treatment option. A randomized controlled trial (FIRM-ACT) evaluating the efficacy of EDP-M showed progression-free survival (PFS) was 5.0 months, overall survival (OS) was 14.8 months, the response rate was 19%, and adrenal insufficiency occurred in 3.4% of patients. However, the efficacy and safety of this regimen in Asia are not fully reported.

METHODS

We retrospectively analyzed 43 patients diagnosed with metastatic ACC at the National Cancer Center Hospital between 1997 and 2020. We evaluated PFS, OS, and response in 17 patients who received EDP-M as first-line therapy.

RESULTS

The median age at treatment initiation was 45 years (range 18-74). Eight patients (47%) had autonomous hormone production, including six patients with hypercortisolism. The best response of partial response and stable disease was seen in two (12%) and ten (59%) patients, respectively. The median PFS was 6.2 months [95% confidence interval (CI): 4.3-10.0]. The median OS was 15.4 months (95% CI 11.6-not reached). Three patients received only one cycle due to adverse effects associated with hypercortisolism. Grade 3/4 adverse events associated with adrenal insufficiency occurred in three (17%) cases, resulting in EDP-M discontinuation.

CONCLUSIONS

The EDP-M regimen had similar PFS to that observed in FIRM-ACT. Adrenal insufficiency was more frequent in the current study, but this could be managed with supportive endocrinological care such as cortisol replacement.

Nomogram for the Prediction of Intrahospital Mortality Risk of Patients with ST-Segment Elevation Myocardial Infarction Complicated with Hyperuricemia: A Multicenter Retrospective Study

Purpose

This study aimed to establish an accurate and easy predictive model for ST-segment elevation myocardial infarction (STEMI) patients with hyperuricemia, using readily available features to estimate intrahospital mortality risk.

Patients and Methods

This was a multicenter retrospective study involving the development of risk prediction models for intrahospital mortality among all STEMI patients with hyperuricemia from Zunyi Medical University Chest Pain Center’s specialized alliance between January 1, 2016 and June 30, 2020. The primary outcome was intrahospital mortality. A total of 48 candidate variables were considered from demographic and clinical data. The least absolute shrinkage and selection operator (LASSO) was used to develop a nomogram. Concordance index values, decision curve analysis, the area under the curve (AUC), and clinical impact curves were examined. In this study, 489 patients with STEMI were included in the training dataset and an additional 209 patients from the 44 chest pain centers were included in the test cohort. B-type natriuretic peptides, α-hydroxybutyrate dehydrogenase (α-HBDH), cystatin C, out-of-hospital cardiac arrest (OHCA), shock index, and neutrophil-to-lymphocyte ratio were associated with intrahospital mortality and included in the nomogram.

Results

The model showed good discrimination power, and the AUC generated to predict survival in the training set was 0.875 (95% confidence interval, 0.825–0.925). In the validation set, the AUC of survival predictions was 0.87 (95% confidence interval, 0.792–0.947). Calibration plots and decision curve analysis showed good model performance in both datasets. A web-based calculator (https://bzxzmu.shinyapps.io/STEMI-with-Hyperuricemia-intrahospital-mortality/) was established based on the nomogram model, which was used to measure the levels of OHCA, neutrophil-to-lymphocyte ratio, shock index, α-HBDH, cystatin C, and B-type natriuretic peptides.

Conclusion

For practical applications, this model may prove clinically useful for personalized therapy management in patients with STEMI with hyperuricemia.

Derivation and validation of a model to predict acute kidney injury following cardiac surgery in patients with normal renal function

BACKGROUND

The study aimed to construct a clinical model based on preoperative data for predicting acute kidney injury (AKI) following cardiac surgery in patients with normal renal function.

METHODS

A total of 22,348 consecutive patients with normal renal function undergoing cardiac surgery were enrolled. Among them, 15,701 were randomly selected for the training group and the remaining for the validation group. To develop a model visualized as a nomogram for predicting AKI, logistic regression was performed with variables selected using least absolute shrinkage and selection operator regression. The discrimination, calibration, and clinical value of the model were evaluated.

RESULTS

The incidence of AKI was 25.2% in the training group. The new model consisted of nine preoperative variables, including age, male gender, left ventricular ejection fraction, hypertension, hemoglobin, uric acid, hypomagnesemia, and oral renin-angiotensin system inhibitor and non-steroidal anti-inflammatory drug within 1 week before surgery. The model had a good performance in the validation group. The discrimination was good with an area under the receiver operating characteristic curve of 0.740 (95% confidence interval, 0.726-0.753). The calibration plot indicated excellent agreement between the model prediction and actual observations. Decision curve analysis also showed that the model was clinically useful.

CONCLUSIONS

The new model was constructed based on nine easily available preoperative clinical data characteristics for predicting AKI following cardiac surgery in patients with normal kidney function, which may help treatment decision-making, and rational utilization of medical resources.

Establishment of a Prognostic Nomogram for Patients With Locoregionally Advanced Nasopharyngeal Carcinoma Incorporating TNM Stage, Post-Induction Chemotherapy Tumor Volume and Epstein-Barr Virus DNA Load

Objectives

To establish and validate an effective nomogram to predict clinical outcomes for patients with locoregionally advanced nasopharyngeal carcinoma (LA-NPC).

Materials and Methods

The clinicopathological parameters and follow-up information of 402 locoregionally advanced NPC patients (training cohort, n = 302; validation cohort, n = 100) were retrospectively enrolled. The nomogram was built with the important prognostic variables identified by Cox regression analysis. Overall survival (OS) and progression-free survival (PFS) were the primary and secondary endpoints, respectively. The predictive power and clinical utility of the nomogram were assessed using the Harrell concordance index (C-index), calibration curve, and decision curve analysis. We compared the eighth staging system model with the nomogram to analyze whether the model could improve the accuracy of prognosis

Results

Epstein–Barr virus (EBV) DNA load, the gross tumor volume (GTVnx), and cervical lymph node tumor volume (GTVnd) after induction chemotherapy were the independent predictors of OS and PFS. The calibration curves indicated superb agreement between the nomogram-predicted probabilities and observed actual probabilities of survival. The C-index and area under the receiver operator characteristic curve (AUC) of the nomogram integrating these significant factors and N stage, and TNM stage were higher than those of the eighth TNM system alone. In addition, the decision curve analyses demonstrated the clinical value and higher overall net benefit of the nomogram. High-risk groups identified by the nomogram had significantly poorer OS and PFS than the low-risk group (p < 0.05).

Conclusions

The multidimensional nomogram incorporating TNM stage, EBV DNA load, and tumor volume after induction chemotherapy led to a more precise prognostic prediction and could be helpful for stratifying risk and guiding treatment decisions in locoregionally advanced NPC patients who have undergone induction chemotherapy and concurrent chemoradiation.

Development and validation of a nomogram for predicting stroke risk in rheumatoid arthritis patients

We developed and validated a nomogram to predict the risk of stroke in patients with rheumatoid arthritis (RA) in northern China. Out of six machine learning algorithms studied to improve diagnostic and prognostic accuracy of the prediction model, the logistic regression algorithm showed high performance in terms of calibration and decision curve analysis. The nomogram included stratifications of sex, age, systolic blood pressure, C-reactive protein, erythrocyte sedimentation rate, total cholesterol, and low-density lipoprotein cholesterol along with the history of traditional risk factors such as hypertensive, diabetes, atrial fibrillation, and coronary heart disease. The nomogram exhibited a high Hosmer–Lemeshow goodness-for-fit and good calibration (P > 0.05). The analysis, including the area under the receiver operating characteristic curve, the net reclassification index, the integrated discrimination improvement, and clinical use, showed that our prediction model was more accurate than the Framingham risk model in predicting stroke risk in RA patients. In conclusion, the nomogram can be used for individualized preoperative prediction of stroke risk in RA patients.