Intrinsic and extrinsic flaws of the nomogram predicting bone-only metastasis in women with early breast cancer: An external validation study

A nomogram for predicting liver metastasis in patients with gastric gastrointestinal stromal tumor

BACKGROUND

Liver metastasis (LIM) is an important factor in the diagnosis, treatment, follow-up, and prognosis of patients with gastric gastrointestinal stromal tumor (GIST). There is no simple tool to assess the risk of LIM in patients with gastric GIST. Our aim was to develop and validate a nomogram to identify patients with gastric GIST at high risk of LIM.

METHODS

Patient data diagnosed as having gastric GIST between 2010 and 2019 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database and randomly divided into training cohort and internal validation cohort in a 7:3 ratio. For external validation, retrospective data collection was performed on patients diagnosed as having gastric GIST at Yunnan Cancer Center (YNCC) between January 2015 and May 2023. Univariate and multivariate logistic regression analyses were used to identify independent risk factors associated with LIM in patients with gastric GIST. An individualized LIM nomogram specific for gastric GIST was formulated based on the multivariate logistic model; its discriminative performance, calibration, and clinical utility were evaluated.

RESULTS

In the SEER database, a cohort of 2341 patients with gastric GIST was analyzed, of which 173 cases (7.39%) were found to have LIM; 239 patients with gastric GIST from the YNCC database were included, of which 25 (10.46%) had LIM. Multivariate analysis showed tumor size, tumor site, and sex were independent risk factors for LIM (P < .05). The nomogram based on the basic clinical characteristics of tumor size, tumor site, sex, and age demonstrated significant discrimination, with an area under the curve of 0.753 (95% CI, 0.692-0.814) and 0.836 (95% CI, 0.743-0.930) in the internal and external validation cohort, respectively. The Hosmer-Lemeshow test showed that the nomogram was well calibrated, whereas the decision curve analysis and the clinical impact plot demonstrated its clinical utility.

CONCLUSION

Tumor size, tumor subsite, and sex were significantly correlated with the risk of LIM in gastric GIST. The nomogram for patients with GIST can effectively predict the individualized risk of LIM and contribute to the planning and decision making related to metastasis management in clinical practice.

Nomogram for predicting the risk of bone metastasis in breast cancer: a SEER population-based study

Background

Bone is the most common metastasis site of breast cancer. The prognosis of bone metastasis is better than other distant metastases, but patients with skeletal related events (SREs) have a poor quality of life, high healthcare costs and low survival rates. This study aimed to establish an effective nomogram for predicting risk of bone metastasis of breast cancer.

Methods

The nomogram was built on 4,895 adult/female/primary invasive breast cancer patients with complete clinicopathologic information, captured by the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015. Five biological factors (age, grade, histologic type, surgery of breast lesions and subtypes) were assessed with logistic regression to predict the risk of bone metastases. The predictive accuracy and discriminative ability of the nomogram were determined by the Receiver Operating Characteristic (ROC) curves and the calibration plot. Results were validated on a separate 2,093 cohort using bootstrap resampling from 2010 to 2015 as an internal group and a retrospective study on 120 patients in the First Affiliated Hospital of China Medical University from 2010 to 2014 at the same situation as an external group.

Results

On multivariate logistic regression of the primary cohort, independent factors for bone metastases were age, grade, histologic type, surgery of breast lesions and subtypes, which were all selected into the nomogram. The calibration plot for probability of incidence showed good agreement between prediction by nomogram and two observations. The ROC curves presented a good statistical model for risk of bone metastasis, and the corresponding AUC value of the development group, internal validation group and external validation group were 0.678, 0.689 and 0.704 respectively.

Conclusions

The proposed nomogram resulted in more-accurate prognostic prediction for breast cancer patients with bone metastases.

A nomogram based on serum bilirubin and albumin levels predicts survival in gastric cancer patients

Decreases in serum bilirubin and albumin levels are associated with poorer prognoses in some types of cancer. Here, we examined the predictive value of serum bilirubin and albumin levels in 778 gastric cancer patients from a single hospital in China who were divided among prospective training and retrospective validation cohorts. X-tile software was used to identify optimal cutoff values for separating training cohort patients into higher and lower overall survival (OS) groups, based on total bilirubin (TBIL) and albumin levels. In univariate analysis, tumor grade and TNM stage were associated with OS. After adjusting for tumor grade and TNM stage, TBIL and albumin levels were still clearly associated with OS. These results were confirmed in the 299 patients in the validation cohort. A nomogram based on TBIL and albumin levels was more accurate than the TNM staging system for predicting prognosis in both cohorts. These results suggest that serum TBIL and albumin levels are independent predictors of OS in gastric cancer patients, and that an index that combines TBIL and albumin levels with the TNM staging system might have more predictive value than any of these measures alone.

Radiation for persistent or recurrent epithelial ovarian cancer: a need for reassessment

Purpose

The role of radiotherapy (RT) was largely deserted after the introduction of platinum-based chemotherapy, but still survival rates are disappointingly low. This study focuses on assessing the clinical efficacy of RT in relation to chemotherapy resistance.

Materials and Methods

From October 2002 to January 2015, 44 patients were diagnosed with epithelial ovarian cancer (EOC) and treated with palliative RT for persistent or recurrent EOC. All patients received initial treatment with optimal debulking surgery and adjuvant platinum-based chemotherapy. The biologically effective dose (BED) was calculated with α/β set at 10. Ninety-four sites were treated with RT with a median BED of 50.7 Gy (range 28.0 to 79.2 Gy). The primary end-point was the in-field local control (LC) interval, defined as the time interval from the date RT was completed to the date any progressive or newly recurring disease within the RT field was detected on radiographic imaging.

Results

The median follow-up duration was 52.3 months (range 7.7 to 179.0 months). The 1-year and 2-year in-field LC rates were 66.0% and 55.0%, respectively. Comparisons of percent change of in-field tumor response showed similar distribution of responses among chemoresistant and chemosensitive tumors. On multivariate analysis of predictive factors for in-field LC analyzed by sites treated, BED ≥ 50 Gy (hazard ratio, 0.4; confidence interval, 0.2–0.9; p = 0.025) showed better outcomes.

Conclusion

Regardless of resistance to platinum-based chemotherapy, RT can be a feasible treatment modality for patients with persistent of recurrent EOC. The specific role of RT using updated approaches needs to be reassessed.