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Background : The major salivary gland squamous cell carcinoma is a rare head and neck tumor, often accompanied by lymph node metastasis. Even if the patient undergoes surgery, the prognosis remains unsatisfactory. To explore the prognostic factors of postoperative major salivary gland squamous cell carcinoma to establish a prognostic risk stratification model to guide clinical practice. Methods: Patients’ information was retrieved from the Surveillance, Epidemiology, and End Results database from 2004 to 2018. Optimal cutoff points were determined using X-tile software, and overall survival and disease-specific survival were calculated by the Kaplan-Meier method. Independent prognostic factors affecting the overall survival and disease-specific survival were identified by multivariate analysis, and corresponding 2 nomogram models were constructed. The discriminative ability and calibration of nomograms were evaluated by the Concordance index, area under curves, and calibration plots. Results: A total of 815 patients with postoperative major salivary gland squamous cell carcinoma were enrolled. The cutoff values for the number of lymph nodes were 2, and the cutoff values for the lymph node ratio were 0.11 and 0.5, respectively. Age, T stage, tumor size, lymph nodes, lymph node ratio, and radiotherapy were prognostic factors for overall survival and disease-specific survival. Nomograms for disease-specific survival and overall survival were established and showed favorable performance with a higher Concordance index and area under curves than that of the tumor–node–metastasis stage and Surveillance, Epidemiology, and End Results stage. The calibration plots of 1-, 3-, and 5-year overall survival and disease-specific survival also exhibited good consistency. What's more, patients were divided into low-, moderate-, and high-risk groups according to the scores calculated by the models. The overall survival and disease-specific survival of patients in the high-risk group were significantly worse than those in the moderate- and low-risk group. Conclusions: Our nomogram integrated clinicopathological features and treatment modality to demonstrate excellent performance in risk stratification and prediction of survival outcomes in patients with major salivary gland squamous cell carcinoma after surgery, with important clinical value.

The current state of oncology medical services is not encouraging and is unable to fully meet the needs of patients with cancer. In recent years, rapidly developing artificial intelligence technology and gradual advancements in mobile phones, sensors, and wearable devices, which have made these more compact, affordable, and popular, have greatly expanded the development of digital medicine. Digital medicine refers to clinical evidence‐based technology and products with a direct impact on disease management and research. Integrating digital medicine into clinical practice has the advantages of broader applicability, greater cost‐effectiveness, better accessibility, and improved diagnostic and therapeutic performance. Digital medicine has emerged in different clinical application scenarios, including cancer prevention, screening, diagnosis, and treatment, as well as clinical trials. Additionally, big data generated from digital medicine can be used to improve levels of clinical diagnosis and treatment. However, digital medicine also faces many challenges, including security regulation and privacy protection, product usability, data management, and optimization of algorithms. In summary, the application and development of digital medicine in the field of cancer face numerous opportunities and challenges.

Aim: To identify clinical and genetic variants associated with early-onset cardiac toxicity with a low cumulative dose of chemotherapy drugs in breast cancer. Methods: A total of 388 recruited patients completed routine blood, liver and kidney function, D-dimer, troponin T, brain natriuretic peptide (BNP) or N-terminal prohormone of BNP, ECG and echocardiography tests before and after adjuvant chemotherapy. 25 single-nucleotide polymorphisms (SNPs) were tested. Results: A total of 277 adjuvant chemotherapy-related cardiac toxicity events were recorded in 180 patients (46.4%). Anthracycline-containing chemotherapy (odds ratio: 1.848; 95% CI: 1.135–3.008; p = 0.014) and the SLC28A3 rs885004 GG genotype (odds ratio: 2.034; 95% CI: 1.189–3.479; p = 0.010) were found to be associated with overall cardiac toxicity. The final predictive risk model consisting of clinical risk factors and SNPs was better than SNP alone (p = 0.006) or clinical risk factor alone (p = 0.065). Conclusion: On the basis of clinical factors, a prediction model with genetic susceptibility factors can better predict early-onset cardiac toxicity.

Background To investigate the value of lymph node ratio (LNR) for postoperative major salivary duct carcinoma (MSDC) and to establish a model for prognosis assessment and treatment optimization. Methods Data of MSDC were retrieved in public database, and prognostic factors were identified by univariate and multivariate analyses. A nomogram and risk stratification system were constructed. Results Four hundred and eleven eligible patients were included (training cohort vs. validation cohort: 287: 124). LNR ≥0.09 was associated with worse overall survival (OS). Age at diagnosis, sex, T stage, and LNR were identified as prognostic factors and integrated into nomogram. Low‐risk patients were found to have better OS than high‐risk patients. Furthermore, postoperative radiotherapy (PORT) significantly improved OS in the high‐risk subgroup, but chemotherapy did not confer a long‐term survival benefit. Conclusions A nomogram model integrating LNR could better assess postoperative prognosis and risk stratification in MSDC, and identify patients who might benefit from PORT to avoid overtreatment.