Nomogram prediction for the overall survival and cancer-specific survival of patients diagnosed with Merkel cell carcinoma

A nomogram for predicting the overall survival in rectal cancer patients after total neoadjuvant therapy

BACKGROUND

Total neoadjuvant therapy (TNT) has been recommended by the National Comprehensive Cancer Network for treating locally advanced rectal cancer (LARC), but extremely rare studies have focused on establishing nomograms to predict the prognosis in these patients after TNT. We aimed to develop a nomogram to predict overall survival (OS) in rectal cancer patients who underwent TNT.

METHODS

In retrospective cohort study, we extract the data of the rectal cancer patients from the SEER database between 2010 and 2015, including demographic information and tumor characteristics. The cohort was divided into training set and validation set based on a ratio of 7:3. Univariate logistic regression analysis was utilized for the comparison of variables in training set. Candidate variables with P < 0.1 in training set was entered into the best subset selection, LASSO regression and Boruta feature selection. Finally, the selected variables significantly associated with the 3-year, 5-year, and 8-year OS were used to build a nomogram, followed by validation using receiver operating characteristic (ROC) curve, area under the curve (AUC), and calibration curve.

RESULTS

A total of 3265 rectal cancer patients (training set: 2285; test set: 980) were included in the present study. A nomogram was developed to predict the 3-year, 5-year, and 8-year OS based on age, household income, total number of in situ/malignant tumors, CEA, T stage, N stage and perineural invasion. The nomogram showed good efficiency in predicting the 3-year, 5-year and 8-year OS with good AUC for the training set and test set, respectively.

CONCLUSION

We established a nomogram for predicting the 3-year, 5-year, and 8-year OS of the rectal cancer patients, which showed good prediction efficiency for the OS after TNT.

Patterns of Care and Data Quality in a National Registry of Black and White Patients with Merkel Cell Carcinoma

Merkel Cell Carcinoma (MCC) is a rare cancer most commonly affecting White patients; less is known for Black patients. We aim to report presentation, treatment, and quality of registry data by race with a secondary endpoint of overall survival. We conducted a retrospective cohort analysis between 2006−2017 via the National Cancer Database of Black and White MCC patients with and without known staging information. Multivariable logistic, proportional odds logistic, and baseline category logistic regression models were used for our primary endpoint. Multivariable Cox regression was used to interrogate overall survival. Multiple imputation was used to mitigate missing data bias. 34,503 patients with MCC were included (2566 Black patients). Black patients were younger (median age 52 vs. 72, p < 0.0001), had higher rates of immunosuppression (28% vs. 14%, p = 0.0062), and were more likely to be diagnosed at a higher stage (proportional OR = 1.41, 95% CI 1.25−1.59). No differences were noted by race across receipt of definitive resection (DR), though Black patients did have longer time from diagnosis to DR. Black patients were less likely to receive adjuvant radiation. Black patients were more likely to have missing cancer stage (OR = 1.69, CI 1.52−1.88). Black patients had decreased adjusted risk of mortality (HR 0.73, 0.65−0.81). Given the importance of registry analyses for rare cancers, efforts are needed to ensure complete data coding. Paramount to ensuring equitable access to optimal care for all is the recognition that MCC can occur in Black patients.

Development and validation of tumor-size-stratified prognostic nomograms for patients with uterine sarcoma: A SEER database analysis

BACKGROUND

Tumor-size-stratified analysis on the prognosis of uterine sarcoma is insufficient. This study aimed to establish the tumor-size-stratified nomograms to predict the 3- and 5-year overall survival (OS) of patients with uterine sarcoma.

METHODS

The data analyzed in this study were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. We collected data from patients with uterine sarcoma diagnosed between 2004 and 2015. According to the median tumor size of 7.8 cm, the enrolled patients were divided into two tumor size (TS) groups: TS <7.8 cm and TS ≥7.8 cm. Patients in each group were randomly divided into the training and validation cohorts with a ratio of 7:3. Chi-square test was used to compare differences between categorical variables. Multivariate Cox regression models were used to identify significant predictors. We calculated the concordance index (C-index) and the area under the receiver operating characteristics curve (AUC) to validate the nomograms.

RESULTS

Compared with TS <7.8 cm group, TS ≥7.8 cm group had more patients of 45-64 years group, higher black race prevalence, higher proportion of myometrium tumor, higher stage, and higher grade; In the TS <7.8 cm training cohort, six variables (age, race, marital status, tumor primary site, stage, and grade) were identified as significantly associated with OS in multivariate analysis. However in the TS ≥7.8 cm training cohort, only four variables (surgery on primary site, tumor size, stage, and grade) were significantly identified; The C-index of two nomograms were 0.80 and 0.73 in training cohorts, respectively, and the AUC values for 3- and 5-year OS predictions in training cohorts were all above 0.80. Similar results were observed in validation cohorts.

CONCLUSIONS

This study found that the significant prognostic factors were different between two tumor size groups of uterine sarcoma patients. The tumor-size-stratified nomograms, which we constructed and validated, might be useful to predict the probability of survival for patients with uterine sarcoma.

Effects of surgery on survival of patients aged 75 years or older with Merkel cell carcinoma

Objective

To investigate whether surgery improves prognosis in elderly patients with Merkel cell carcinoma (MCC).

Materials/Methods

Data of all patients with MCC diagnosed between 2004 and 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Differences in baseline characteristics were analyzed among the age groups (75–80, 80–85, and ≥85 years). Multivariate Cox proportional hazards analysis was used to assess the effects of each variable on patient outcomes. The Kaplan–Meier curves were employed to evaluate MCC overall survival (OS) and MCC‐specific survival (MSS).

Results

A total of 1156 of patients with MCC met the inclusion and exclusion criteria. The surgery rate decreased with age (75–80, 80–85, and ≥85 years were 93.3%, 91.1%, and 88.7%, respectively; p = 0.082). Multivariate Cox proportional hazards analysis showed that the OS of patients in the 80–85 years group (hazard ratio [HR] = 1.39; 95% confidence interval [CI] = 1.14–1.70; p = 0.001) and the ≥85 years group (HR = 2.18; 95% CI = 1.80–2.63; p < 0.0001) was worse than that in the 75–80 years group. Compared with the non‐surgery groups, the HR for the surgery group was 0.75 for OS (95% CI = 0.56–1.00; p = 0.048) and 0.73 for MSS (95% CI = 0.48–1.10; p = 0.130). Subgroup analyses showed that patients aged ≥85 years undergoing surgery had better OS (HR = 0.65; 95% CI = 0.45–0.95; p = 0.024).

Conclusions

MCC patients aged 75 years and older would benefit from surgical resection. However, surgical resection should be performed cautiously, and larger prospective clinical trials are needed to further verify these findings.

Postoperative Radiotherapy in Stage I-III Merkel Cell Carcinoma

BACKGROUND

Postoperative radiotherapy (PORT) is currently recommended for the treatment of Merkel cell carcinoma. Nevertheless, deviations occur frequently due to the generally elderly and frail patient population. We aimed to evaluate the influence of PORT on survival in stage I-III MCC patients treated in the Netherlands.

METHODS

Patients were included retrospectively between 2013 and 2018. Fine-Gray method was used for cumulative incidence of recurrence and MCC-related survival, cox regression was performed for overall survival (OS). Analyses were performed in patients with clinical (sentinel node biopsy [SN] not performed) stage I/II (c-I/II-MCC), pathologic (SN negative) stage I/II (p-I/II-MCC) and stage III MCC (III-MCC), separately. Propensity score matching (PSM) was performed to assess confounding by indication.

RESULTS

In total 182 patients were included, 35 had p-I/II-MCC, 69 had c-I/II-MCC and 78 had III-MCC. Median follow up time was 53.5 (IQR 33.4-67.4), 30.5 (13.0-43.6) and 29.3 (19.3-51.0) months, respectively. Multivariable analysis showed PORT to be associated with less recurrences and improved OS, but not with MCC-related survival. In stage III-MCC, extracapsular extension (sub-distribution hazard [SDH] 4.09, p=0.012) and PORT (SDH 0.45, p=0.044) were associated with recurrence, and ≥4 positive lymph nodes (SDH 3.24, p=0.024) were associated with MCC-related survival.

CONCLUSIONS

PORT was associated with less recurrences and improved OS in patients with stage I-III MCC, but not with improved MCC-related survival. Trends in OS benefit are likely to be caused by selection bias suggesting further refinement of criteria for PORT is warranted, for instance by taking life expectancy into account.

A novel nomogram based on a retrospective study of 346 patients to predict the recurrence risk of condyloma acuminatum after 5-aminolevulinic acid photodynamic therapy

Condyloma acuminatum (CA) is a sexually transmitted disease caused by human papillomavirus (HPV) often with high recurrence rate after treatment. This study aimed to construct and evaluate a nomogram model containing three clinical parameters to predict the recurrence risk of CA after 5-aminolevulinic acid photodynamic therapy (ALA-PDT). A predictive model was established based on a training cohort of 346 CA patients treated with ALA-PDT between January 2013 and July 2018. A validation cohort of 123 CA patients was recruited from August 2018 to December 2019. The least absolute shrinkage and selection operator (LASSO) regression model was used to optimize the clinical feature selection. A nomogram predicting the recurrence of CA after ALA-PDT was constructed based on the predictors identified by LASSO regression. C-index and area under the curve (AUC) values were used to evaluate the discrimination. Calibration was evaluated with a calibration curve. The net benefit was performed via decision curve analysis (DCA). In the training cohort, 55 (15.89%) patients experienced recurrences after ALA-PDT. Predictors selected by LASSO regression were concomitant human immunodeficiency virus (HIV) infection [Hazard ratio (HR) = 4.4; 95% confidence interval (CI), 2.5-7.9; p < 0.001], skin and mucosa as affected area (HR = 1.7; 95% CI, 0.9-3.1; p = 0.109), and more than one time of CO₂ laser therapy (HR = 6.3; 95% CI, 2.8-13.9; p < 0.001). The nomogram showed a good performance in predicting recurrence as the C-indexes were 0.843 (95% CI, 0.799-0.887) in the training cohort, and 0.831 (95% CI, 0.727-0.934) in the validation cohort. The AUCs of the nomogram were 0.85 in training and 0.8 in validation. DCA confirmed the nomogram was clinically useful when the intervention was determined at the non-adherence possibility threshold of 5%. This nomogram can provide individualized prediction for the recurrence risk of CA in patients treated by ALA-PDT.