Wang, Ming

Purpose This study aimed to develop and validate a tool to predict the primary tumor site in patients with metastatic cancer of unknown primary using demographic and clinical variables, including imaging-derived sites of metastasis, without pathology or laboratory data. Methods In this population-based study, data were extracted from the SEER database. Patients diagnosed between 2010 and 2020 with a known primary cancer site, metastatic staging, and metastasis in the bone, liver, brain, and lungs were included. Patients were randomly split into training (70%) and/or testing (30%) sets. A total of 27 primary tumor sites were included. A gradient boosting model was trained to predict the primary tumor site, with random forest and classification tree models evaluated as comparators. Random guess and frequency-weighted guessing models were used for baseline comparison. Results A total of 689,715 patients were included from 9,208,295 queried. The most common primary cancer sites were non–small cell lung cancer (NSCLC) (n = 211,338), intestines (n = 64,187), and pancreas (n = 60,310). The baseline models achieved Top-5 accuracies of 0.179 for a random guess and 0.476 for a frequency-weighted guess. The gradient boosting model achieved Top-1, Top-3, and Top-5 accuracies of 0.40 ± 0.001, 0.680 ± 0.001, and 0.790 ± 0.001, respectively, across 100 Monte-Carlo replicates. Top-5 accuracy was highest for primary NSCLC (0.990 ± 0.001) and intestinal cancer (0.900 ± 0.003). Our model was most influenced by sex (gain = 0.27) and metastasis to bone (gain = 0.20). A web app was constructed: primarycancerpredictor.netlify.app. Conclusion This study developed and evaluated a gradient boosting machine learning model and a user-friendly web tool to aid in the diagnosis of cancer of unknown primary.

Abstract Background: Sexual and gender minority (SGM) representation is growing in the United States. This study estimated the future SGM cancer burden amidst shifting cancer patterns. Methods: Age-specific incidence data for breast, prostate, colorectal, lung, and melanoma were obtained from the Surveillance, Epidemiology, and End Results Program’s 12-registry database. Nordpred age-period-cohort models projected incidence through 2040 to 2044. Rates were applied to US Census population estimates and generation- and sex-specific SGM identification proportions from Gallup’s 2023 to 2024 surveys. Prophet was used for sensitivity analysis. Results: At ages 55 to 59, breast cancer cases among Millennial SGMs were 3,672% higher than among Silent Generation SGMs (34,850 vs. 924 cases), melanoma cases were 1,061% higher (5,526 vs. 476 cases), and colorectal cancer cases were 2,206% higher (23,594 vs. 1,023 cases). Compared with Generation X, Millennial prostate cancer cases were 142% higher (8,100 vs. 3,344 cases), and lung cancer cases were 169% higher (5,451 vs. 2,029 cases). By 2040 to 2044, Millennials were projected to account for 68.4% of breast cancer cases and 59.7% of colorectal cancer cases among SGMs. Conclusions: At ages 55 to 59, the 5-year cancer burden was projected to be 15 times higher among Millennials than Silent Generation SGMs (77,521 vs. 5,134 cases), driven primarily by the larger SGM population in younger generations. Oncology systems will need to prepare for the increase in cancer care demand. Impact: These findings identify a substantial generational shift in the SGM cancer burden and may inform oncology workforce capacity, culturally responsive cancer care, and healthcare system preparation for this growing population.

PURPOSE Although outcomes for nonmetastatic cancers have improved since the 1970s, it remains uncertain whether long-term survival has improved among patients presenting with de novo metastatic disease, defined as cancer presenting with distant metastases at the time of initial diagnosis. This study evaluated changes in 5-year survival among patients with de novo metastatic cancer diagnosed in 1976 versus 2015, with a minimum 5-year follow-up through 1981 and 2020, respectively. METHODS Population-based data were obtained from the SEER database. Patients diagnosed with de novo metastatic cancer in 1976 (n = 11,864) and 2015 (n = 26,324) were included. Five-year overall survival (OS) was compared between cohorts, and multivariable logistic regression identified demographic and clinical factors associated with survival. RESULTS The 5-year OS increased significantly from 10.6% in 1976-1981 to 23.6% in 2015-2020 ( P < .001). Survival gains were largest in breast cancer (12.6%-34.2%; P < .001), ovarian cancer (14.4%-32.5%; P < .001), colorectal cancer (3.7%-15.0%; P < .001), and hematologic malignancies (24.3%-53.9%; P < .001). Minimal improvement occurred in pancreatic cancer (0.25%-1.6%; P = .007) and small cell lung cancer (0.8%-3.1%; P = .008). Multivariable analysis demonstrated that older age, male sex, and Black race were associated with lower odds of 5-year survival (all P < .01) CONCLUSION Over the past four decades, long-term survival among patients with de novo metastatic cancer has more than doubled; however, progress remains uneven across cancer types. Gains appear concentrated in malignancies with substantial therapeutic advances, whereas others show persistently poor outcomes. Continued efforts are needed to address disparities and improve survival in resistant cancer types.

Background: Increased facility surgical treatment volume is sometimes associated with improved survival in patients with cancer; however, published studies evaluating volume are heterogeneous and disparate in their patient inclusion and definition of volume. The purpose of this work was to evaluate uniformly the impact of surgical facility volume on survival in patients with cancer. Methods: The National Cancer Database was searched for patients diagnosed in 2004 through 2013 with the 12 cancers most commonly treated surgically. Facilities were stratified by 4 categories using the overall population (low, intermediate, high, and very high), each including 25% of patients, and then stratified by each individual disease site. Five-year postsurgery survival was estimated using both the Kaplan-Meier method and corresponding log-rank tests for group comparisons. Cox proportional hazard models were used to evaluate the effects of facility volume on 5-year postsurgery survival further, adjusted for multiple covariates. Results: A total of 3,923,618 patients who underwent surgery were included from 1,139 facilities. Of these, 40.4% had breast cancer, 12.8% prostate cancer, and 10.0% colon cancer. Most patients were female (65.0%), White (86.4%), and privately insured (51.6%) with stage 0–III disease (64.8%). For all cancers, the risk of death for patients undergoing surgery at very high-volume facilities was 88% of that for those treated at low-volume facilities. Hazard ratios (HRs) were greatest (very high vs low volume) for cancer of the prostate (HR, 0.66; 95% CI, 0.63–0.69), pancreas (HR, 0.75; 95% CI, 0.71–0.78), and esophagus (HR, 0.78; 95% CI, 0.73–0.83), and for melanoma (HR, 0.81; 95% CI, 0.78–0.84); differences were smallest for uterine and non–small cell lung cancers. Overall survival differences were greatest for cancers of the brain, pancreas, and esophagus. Conclusions: Patients treated surgically at higher-volume facilities consistently had improved overall survival compared with those treated at low-volume centers, although the magnitude of difference was cancer-specific.

Abstract Background We hypothesized that the addition of receptor tyrosine kinase inhibitors (RTKis, e.g., lapatinib, erlotinib, cetuximab, bevacizumab, panitumumab) to radiotherapy-based treatment for solid tumors does not increase overall survival but may increase toxicity. Methods Population, Intervention, Control, Outcome, Study Design; Preferred Reporting Items for Systematic Reviews and Meta-Analyses; and Meta-analysis of Observational Studies in Epidemiology methods were used to identify prospective randomized studies including patients with solid tumor cancers treated with radiotherapy with or without RTKis. Extracted variables included use of radiotherapy vs chemoradiotherapy, RTKi type (antibody vs small molecule), outcomes, and toxicities. The primary endpoint was overall survival; the secondary endpoint was grade 3+ toxicity. Random-effects meta-analyses were performed for each outcome measure. All statistical tests were 2-sided. Results A total of 405 studies met the initial search criteria, of which 13 prospective randomized trials of radiotherapy with or without RTKi met the inclusion criteria, encompassing 5678 patients. The trials included cancers of the head and neck (6 trials, 3295 patients), esophagus (3 trials, 762 patients), lung (2 trials, 550 patients), and brain (2 trials, 1542 patients). Three studies evaluated a small molecule and radiotherapy in 949 patients, and 10 studies evaluated antibodies and radiotherapy in 4729 patients. The addition of RTKis to radiotherapy-based treatment did not improve overall survival (hazard ratio = 1.02, 95% confidence interval = 0.90 to 1.15, P = .76) but increased grade 3+ toxicity (relative risk = 1.18, 95% confidence interval = 1.06 to 1.33, P = .009). Conclusions The addition of RTKis to radiotherapy does not improve survival and worsens toxicity.