The Predictive Accuracy of PREDICT:A Personalized Decision-Making Tool for Southeast Asian Women With Breast Cancer

A predictive model of survival in early-stage medullary breast carcinoma: a population-based study.

INTRODUCTION This study aimed to establish a predictive model for overall survival (OS) in early-stage medullary breast carcinoma (MedBC). METHODS Clinical data for 606 355 patients with breast cancer were extracted from the Surveillance, Epidemiology, and End Results (SEER) database, along with data for 244 patients with MedBC from electronic medical records of the National Cancer Center of China. Univariate and multivariable Cox regression analyses were conducted to identify prognostic variables. Survival outcomes and model performance were evaluated. RESULTS In total, 650 and 188 patients were included in the SEER and real-world cohorts, respectively. In the real-world cohort, the median Ki-67 index was 70%. Overall survival was not significantly associated with Ki-67 index (P=0.09) or family history of breast cancer (P=0.1). A predictive model for OS was established in the training cohort, incorporating age, tumour (T) stage, nodal (N) stage, and chemotherapy. The overall C-index was 0.76. Area under the curve (AUC) values were 0.83, 0.76, 0.75, and 0.76 for 1-, 3-, 5-, and 10-year OS, respectively. In the internal validation cohort, the C-index was 0.86; AUC values were 0.78 and 0.83 for 3- and 5-year OS, respectively. In the external validation cohort, the C-index was 0.90; AUC values were 0.85, 0.85, and 0.84 for 3-, 5-, and 10-year OS, respectively. The low-risk group had significantly better OS than the high-risk group across training and validation cohorts (P<0.05). CONCLUSION A clinical model incorporating age (≥65 years), T stage (T3/T4), N stage (N2/N3), and chemotherapy (no) was developed to predict inferior OS in early-stage MedBC.

Usefulness of Prognostic Stage in High-Risk Early Luminal Breast Cancer

Introduction: Breast cancer remains the most prevalent malignancy among women worldwide, with prognostic outcomes and therapeutic responses differing considerably across subtypes. The conventional staging framework developed by the Union for International Cancer Control (UICC), based on the Tumor, Node, Metastasis classification, reflects anatomical stage (AS) but overlooks biological characteristics. To address this limitation, the American Joint Committee on Cancer (AJCC) introduced the Prognostic Stage (PS) in its 8th edition, which integrates biomarkers including estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor 2 (HER2), and histological grade (HG). This study aimed to assess and compare the prognostic utility of UICC AS and AJCC PS in patients with high-risk luminal breast cancer. Methods: This retrospective study included patients who underwent surgery for ER-positive, HER2-negative breast cancer at Tokyo Metropolitan Komagome Hospital from 2011 to 2018. High-risk classification was defined based on MonarchE trial criteria: axillary lymph node metastasis, tumor diameter ≥5 cm, HG3, or Ki-67 ≥20%. Staging was performed using both UICC AS and AJCC PS, and prognostic values were evaluated via Kaplan-Meier survival analysis. Results: Among 105 eligible cases, 43 (41%) were downstaged when reclassified from UICC AS to AJCC PS. While UICC AS failed to yield significant stratification in terms of invasive disease-free survival (IDFS) and distant recurrence-free survival (DRFS), AJCC PS demonstrated significant prognostic discrimination (IDFS p = 0.014; DRFS p = 0.004). Conclusions: American Joint Committee on Cancer PS offers superior prognostic stratification compared to UICC AS in high-risk luminal breast cancer. Its incorporation into clinical practice may enable more personalized treatment approaches, particularly when identifying candidates for adjuvant abemaciclib therapy. Further validation through larger, prospective studies is warranted.

Risk prediction model for brain metastasis risk among patients diagnosed with primary gastrointestinal cancers.

A Clinical Score to Identify Individuals at High Risk of Pancreatic Cancer in the General Population

Background/Objectives: Early detection of pancreatic cancer (PC) remains challenging due to the lack of effective screening tools. We aimed to develop a clinically applicable model to identify individuals at high risk of PC using routine health check-up data. Methods: In a 1:4 matched case–control study (111 cases and 439 controls) using data collected between 2010 and 2018, PC cases were defined as individuals diagnosed with PC within 2 years of a health check-up. A model was developed using conditional logistic regression and validated in an independent cohort of 52,043 individuals (40 PC cases; 2019–2021). Results: Five risk factors were identified: carbohydrate antigen 19-9 ≥ 39 U/mL, hemoglobin A1c ≥ 6.5%, alkaline phosphatase > 110 IU/L, weight loss ≥ 5%, and dyspepsia. A 12-point risk scoring system was constructed, with an area under the curve of 0.784 in the development and 0.841 in the validation cohort. At a threshold of ≥5, the high-risk group had a significantly higher 2-year incidence of PC than the low-risk group (2.56% vs. 0.047%; p < 0.001), a 54.76-fold risk enrichment, with a negative predictive value of 99.95% and a number-needed-to-follow of 39. Conclusions: This simple, validated model effectively stratifies short-term PC risk using routine data, potentially facilitating targeted surveillance in the general population.

Risk of Developing Subsequent Primary Colorectal Cancers Among Non-Colorectal Cancer Survivors: Implications for Prevention and Screening.

Cancer survivors have an elevated risk of developing subsequent primary cancers, including colorectal cancer (CRC), and may benefit from tailored screening approaches to reduce incidence and morbidity. A retrospective cohort of adults diagnosed with cancer (excluding CRC) in Alberta, Canada from 2000 to 2021 who survived at least 6 months was used to investigate the incidence of CRC compared to the cancer-free population. Incidence rate differences and standardized incidence ratios (SIRs) were used to characterize risk across first primary cancer sites, sexes, age groups, and survivorship periods, as well as according to CRC stage, histology, and subsite. Multivariable Fine-Gray models were used to identify risk factors within site-specific survivorship groups. Among 172,928 cancer survivors, 1812 were diagnosed with CRC during a median follow-up of 4.9 years. Compared to the cancer-free population, survivors had an elevated risk of CRC (SIR = 1.26, 95% CI: 1.20-1.32). The risk of CRC varied across first primary cancer sites but remained elevated among both short- and long-term survivors. Cancer survivors were at an elevated risk of developing late stage (III/IV) CRC compared to the cancer-free population with the highest risk in the proximal colon and among long-term survivors (5+ years). Depending on the first primary cancer site, risk factors for subsequent CRC included older age at diagnosis, male sex, overweight/obese body mass index, earlier stage at diagnosis, and treatment type. These findings demonstrate the importance of improving adherence to CRC screening guidelines among cancer survivors. Greater research is needed to identify high-risk survivorship groups who may require enhanced screening.

Risk of second primary malignancies after bladder cancer diagnosed at a young age: a SEER population-based analysis.