American Journal of Clinical Oncology-Cancer Clinical Trials最新文献

Background: Triple-negative breast cancer (TNBC) is a subtype of breast cancer characterized by the absence of expression of estrogen receptor, progesterone receptor, or human epidermal growth factor receptor 2. This subtype of breast cancer is known for its high aggressiveness, high metastatic potential, tendency for recurrence, and poor prognosis. Patients with metastatic TNBC (mTNBC) have a poorer prognosis and a higher likelihood of early death (survival time ≤3 months). Therefore, the development of effective individualized survival prediction tools, such as prediction nomograms and web-based survival calculators, is of great importance for predicting the probability of early death in patients with metastatic TNBC.

Methods: Patients diagnosed with mTNBC in the Surveillance, Epidemiology, and End Results database between 2010 and 2015 were included in the model construction. Univariate and multivariate logistic regression analysis was performed to identify risk factors associated with early death in patients with mTNBC and predictive prognostic nomograms were constructed. The accuracy of the nomograms was verified using receiver operating characteristic curves, and GiViTi Calibration belt plots were used to evaluate the model consistency. The clinical applicability of the nomograms was evaluated using decision curve analysis. On the basis of the predictive prognostic nomograms, a network survival rate calculator was developed for individualized survival prediction in patients with mTNBC.

Results: A total of 2230 patients diagnosed with mTNBC were included in the Surveillance, Epidemiology, and End Results database for this study. After strict exclusion criteria, 1428 patients were found to be eligible for the study. All the patients were randomly divided into a training cohort and a validation cohort in a ratio of 7:3. Independent risk factors for mTNBC, including age, tumor size, brain metastasis, liver metastasis, surgery, and chemotherapy, were identified and integrated to construct the prediction nomogram and survival calculator. Results of receiver operating characteristic curves, calibration curves, and decision curve analysis curves from the training and validation cohort confirmed that the developed nomogram and web-based survival calculator in this study could accurately predict the probability of early death in patients with mTNBC.

Conclusions: In this study, we developed a reliable prediction nomogram and web-based survival calculator for predicting the probability of early death in patients with mTNBC. These tools can assist clinical physicians in identifying high-risk patients and developing personalized treatment plans as early as possible.

Objectives: The coronavirus disease 2019 pandemic refocused the cancer community on bringing clinical trials closer to patients and increasing access for traditionally underserved communities. Pandemic-era deregulation increased flexibility with telemedicine visits, less frequent testing, and the ability to have tests done locally. This study evaluates the impact of 2020 cancer clinical trial reform on trial accessibility in rural/underserved regions of the Midwest.

Methods: Publicly available clinicaltrials.gov data was accessed from January 1, 2018 to September 30, 2022 for the 3 leading causes of new cancer cases in Kentucky, Tennessee, Illinois, and Indiana. Interventional trials were categorized based on location using corresponding "Rural-Urban Commuting Area" codes (urban/metropolitan, suburban/micropolitan, small town/rural, and isolated/rural) and categorized as pre versus postpandemic (using March 15, 2020, when national regulatory guidelines were modified). Locations of trial offerings from pre and postpandemic dates were analyzed by paired t test. Comparison of trial location category by state and cancer type was analyzed by 1-way analysis of variance with pairwise multiple comparisons made using the Tukey-Kramer method.

Results: Pandemic-era deregulation had no impact on increasing trial availability in suburban and small-town/rural locales ( P = 0.1259). Only 18% of trials were offered outside of urban areas, with 15% in suburban and 3% in small town/rural areas. Results varied by state ( P < 0.0001) with Illinois offering the most suburban and small-town trial availability (27%) compared with Kentucky, Indiana, and Tennessee (18%, 6%, and 2%, respectively). Trial availability in rural versus urban areas did not differ by cancer type ( P = 0.07197).

Conclusions: More work must be done to increase access to cancer clinical trials in rural and suburban areas of the United States.

Objectives: The Hispanic/Latinx population has consistently faced disparities in oncology access and outcomes with cancer being the leading cause of death in this population. We evaluate recent research in radiation therapy disparities among the Hispanic/Latinx population in the United States since our seminal analysis from 2017.

Methods: A PubMed literature search was conducted for articles published from January 2017 through March 2023. Four term combinations were utilized, including: (1) "Hispanic" and "Radiotherapy" and "Disparities", (2) "Latino" and "Radiotherapy" and "Hispanic", (3) "Hispanic" and "Radiation" and "Disparities", and (4) "Latino" and "Radiation" and "Disparities." Included studies were those taking place in the United States, examined radiation oncology care, and examined health disparities.

Results: Fifty-eight of 245 articles returned met inclusion criteria and spanned 6 disparity-types: (1) Stage at Presentation, (2) Time to Treatment Initiation & Completion, (3) Receipt of Treatment and Guideline-Concordant Care, (4) Geography, (5) Clinical Trial Access and (6) Insurance Barriers and Treatment Center Type. The most common disparity was receipt of treatment and guideline-concordant care (n=39 studies), demonstrating that the Hispanic/Latinx population was less likely to receive guideline-concordant treatment or treatment at all. In additon, studies identified disparities in time to treatment and completion (n=12), geography (n=5), clinical trial access (n=3), and insurance and treatment center access (n=5).

Conclusions: Disparities in radiotherapy access remain prominent for the Hispanic/Latinx population through a multitude of barriers, despite increasing interest in disparities research. Continued health care disparities research with tangible interventions are needed in radiation oncology to properly understand and address this problem.

Objective: To evaluate the survival benefit of combining primary tumor resection (PTR) and chemotherapy in patients with unresectable colorectal mucinous adenocarcinoma with liver metastasis (UCR-MAC-LM).

Methods: We obtained data from the surveillance, epidemiology, and end results database for patients with UCR-MAC-LM from 2010 to 2017. Clinicopathological characteristics were analyzed using the χ2 test. Propensity score matching was performed to balance baseline characteristics. Kaplan-Meier analysis and log-rank tests were used to estimate and compare survival outcomes. Univariate and multivariate Cox regression analyses were conducted to identify the prognostic factors.

Results: A total of 10,178 patients with unresectable colorectal adenocarcinoma with liver metastasis were included, of whom 6.01% (n=612) had UCR-MAC-LM. The UCR-MAC-LM group had a higher proportion of female patients, a greater number of elderly patients, an increased incidence of right colon localization, larger tumor size, and higher T and N staging than the unresectable colorectal non-mucinous adenocarcinoma with liver metastasis group (P<0.05). Multivariate analysis identified several independent prognostic factors (P<0.05). Patients with unresectable colorectal adenocarcinoma with liver metastasis who underwent PTR+C had superior survival rates compared with those who received PTR/C alone or no treatment (cancer-specific survival, P<0.05; overall survival, P<0.05). Subgroup analysis revealed that 17 of 22 groups of patients with UCR-MAC-LM who received PTR+C had significantly prolonged long-term survival compared with those who received PTR/C alone.

Conclusions: This surveillance, epidemiology, and end results-based study indicates that PTR+C may offer a survival advantage for a specific subgroup of patients with UCR-MAC-LM compared with PTR/C alone. Nonetheless, additional clinical trials are necessary to validate these findings.

Background: Thyroid carcinoma (THCA) is the most common malignant endocrine tumor with low mortality and a relatively good prognosis. Immune genes have attracted much attention as molecular markers of THCA prognosis and potential targets of immunotherapy.

Methods: Our study analyzed the transcriptome and clinical data of immune-related genes (IRGs) of THCA in gene expression omnibus, the cancer genome atlas-THCA, and ImmPort databases. By univariate Cox regression analysis, 15 genes were significantly correlated with the survival of patients with THCA. Five IRGs ( NMU, UBE2C, CDKN2A, COL19A1, and GPM6A ) were selected by LASSO regression analysis as independent prognostic factors to construct a disease-free survival-related prognostic risk model.

Results: Kaplan-Meier survival analysis showed that there was a significant difference in disease-free survival between high and low-risk groups. The higher the risk score, the worse the survival of patients. Clinical correlation analysis showed that age and Stage stage of patients were correlated with risk score ( P < 0.05). Quantitative real-time polymerase chain reaction confirmed that there were differences in the expression of 5 IRGs between tumor tissues and normal thyroid tissues. Spearman correlation analysis indicated that the relative expression levels of NMU, CDKN2A, UBE2C, COL19A1 , and GPM6A were positively correlated with programmed death-ligand 1 and recombinant a disintegrin and metalloproteinase with thrombospondin 1.

Conclusion: Based on the bioinformatics method, we constructed a prognosis evaluation model and risk score system of IRGs in THCA, which provided a reference for predicting the prognosis of patients with THCA.

Objective: Low-grade serous ovarian cancer (LGSC) represents 5% of all epithelial ovarian cancers. They are characterized by indolent growth and KRAS and BRAF mutations, differing from high-grade serous ovarian cancer both clinically and molecularly. LGSC has low response rates to traditional systemic therapies, including chemotherapy and hormonal therapy. The objective of this systematic review was to appraise the literature describing the efficacy of MEK inhibitors in the treatment of LGSC.

Methods: A comprehensive search was conducted of the following databases: Medline ALL, EMBASE, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, Web of Sciences, ClinicalTrials.gov, International Clinical Trials Registry Platform (ICFRP), and International Standard Randomized Controlled Trials Number (ISRCTN) Registry. All studies investigating MEKi in the treatment of LGSC in the adjuvant or recurrent setting for patients 18 years of age or older were included. All titles/abstracts were then screened by 2 independent reviewers (A.K. and C.C.). The full-text articles were then screened. All disagreements were resolved by a third independent reviewer (T.Z.). Two independent reviewers (A.K. and C.C.) extracted data from the studies deemed eligible for final review.

Results: A total of 2108 studies were identified in the initial search. Of these, a total of 4 studies met the eligibility criteria for systematic review. In these studies, 416 patients were treated with an MEKi alone. All patients included in the studies were being treated for LGSC in the recurrent setting. Varied results and efficacy of the MEKi were reported in each study.

Conclusions: The results highlighted in this systematic review demonstrate varied responses to MEKi for recurrent LGSC. Further research is needed in this field comparing the efficacy to current therapies, as well as to further evaluate the safety and toxicity profile with long-term use of MEKi.

Objectives: Most patients receiving curative-intent surgery for pancreatic cancer will experience cancer recurrence. However, evidence that postoperative surveillance testing improves survival or quality of life is lacking. We evaluated the use and characteristics of surveillance with serial imaging and CA 19-9 tumor marker testing at an NCI-designated comprehensive cancer center.

Methods: We conducted a retrospective cohort study of patients who entered surveillance after curative-intent resection of pancreatic adenocarcinoma. We abstracted information from the electronic medical record about oncology office visits, surveillance testing (cross-sectional imaging and CA 19-9 tumor marker testing), and pancreatic cancer recurrence, with follow-up through 2 years after pancreatectomy. We conducted analyses to describe the use of surveillance testing and to characterize the sensitivity and specificity of CA 19-9 tumor marker testing for the identification of cancer recurrence.

Results: We identified 90 patients entering surveillance after pancreatectomy. CA 19-9 was the most frequently used surveillance test, followed by CT imaging. Forty-seven patients (52.2%) experienced recurrence within two years of pancreatectomy. Recurrence risk was 58.8% versus 31.8% in patients with elevated versus normal CA 19-9 at diagnosis ( P =0.03). Elevated CA 19-9 at any point during surveillance was significantly associated with 2-year recurrence risk ( P <0.001). Elevated CA 19-9 had a sensitivity of 83% (95% CI 0.72-0.95) and specificity of 87% (0.76-0.98) for identification of recurrence within 2 years of pancreatectomy.

Conclusions: CA 19-9 demonstrates clinical validity for identifying recurrence of pancreatic cancer during surveillance. Surveillance approaches with reduced reliance on imaging should be prospectively evaluated.

Objectives: Artificial intelligence (AI) chatbots are a new, publicly available tool for patients to access health care-related information with unknown reliability related to cancer-related questions. This study assesses the quality of responses to common questions for patients with cancer.

Methods: From February to March 2023, we queried chat generative pretrained transformer (ChatGPT) from OpenAI and Bing AI from Microsoft questions from the American Cancer Society's recommended "Questions to Ask About Your Cancer" customized for all stages of breast, colon, lung, and prostate cancer. Questions were, in addition, grouped by type (prognosis, treatment, or miscellaneous). The quality of AI chatbot responses was assessed by an expert panel using the validated DISCERN criteria.

Results: Of the 117 questions presented to ChatGPT and Bing, the average score for all questions were 3.9 and 3.2, respectively ( P < 0.001) and the overall DISCERN scores were 4.1 and 4.4, respectively. By disease site, the average score for ChatGPT and Bing, respectively, were 3.9 and 3.6 for prostate cancer ( P = 0.02), 3.7 and 3.3 for lung cancer ( P < 0.001), 4.1 and 2.9 for breast cancer ( P < 0.001), and 3.8 and 3.0 for colorectal cancer ( P < 0.001). By type of question, the average score for ChatGPT and Bing, respectively, were 3.6 and 3.4 for prognostic questions ( P = 0.12), 3.9 and 3.1 for treatment questions ( P < 0.001), and 4.2 and 3.3 for miscellaneous questions ( P = 0.001). For 3 responses (3%) by ChatGPT and 18 responses (15%) by Bing, at least one panelist rated them as having serious or extensive shortcomings.

Conclusions: AI chatbots provide multiple opportunities for innovating health care. This analysis suggests a critical need, particularly around cancer prognostication, for continual refinement to limit misleading counseling, confusion, and emotional distress to patients and families.

Objective: The aim of this study was to estimate the recurrence risk based on the number of prognostic factors for patients with stage I uterine endometrioid carcinoma (EC) who underwent surgical lymph node evaluation (SLNE) and were managed with observation.

Methods: We queried our database for women with FIGO-2009 stage I EC who underwent surgical staging including SLNE. Multivariate analysis with stepwise model selection was used to determine independent risk factors for 5-year recurrence-free survival (RFS). Study groups based on risk factors were compared for RFS, disease-specific survival, and overall survival.

Results: A total of 706 patients were identified: median age was 60 years (range, 30 to 93 y) and median follow-up was 120 months. Median number of examined lymph nodes was 8 (range, 1 to 66). 91% were stage IA, 75% had grade 1 and lymphovascular space invasion was detected in 6%. Independent predictors of 5-year RFS included age 60 years and above ( P =0.038), grade 2 ( P =0.003), and grade 3 ( P <0.001) versus grade 1. Five-year RFS for group 0 (age less than 60 y and grade 1) was 98% versus 92% for group 1 (either: age 60 y and older or grade 2/3) versus 84% for group 2 (both: age 60 y and above and grade 2/3), respectively ( P <0.001). Five-year disease-specific survival was 100% versus 98% versus 95%, ( P =0.012) and 5-year overall survival was 98% versus 90% versus 81%, for groups 0, 1, and 2, respectively ( P <0.001).

Conclusions: In patients with stage I EC who received SLNE and no adjuvant therapy, only age 60 years and above and high tumor grade were independent predictors of recurrence and can be used to quantify individualized recurrence risk, whereas lymphovascular space invasion was not an independent prognostic factor in this cohort.

Background: Epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors are standard therapy for patients with non-small cell lung cancer (NSCLC) with EGFR mutation; however, resistance is common. Combinatorial strategies have been explored to improve survival. This meta-analysis assesses the efficacy and safety of combination therapy versus monotherapy in patients with advanced NSCLC who failed first-line EGFR-tyrosine kinase inhibitor treatment.

Methods: We searched randomized controlled trials from PubMed, Web of Science, Google Scholar, Cochrane Library, and ClinicalTrial.gov. The efficacy and toxicity of combination treatment groups were assessed in terms of progression-free survival (PFS), overall response rate (ORR), disease control rate (DCR), and adverse events (AEs).

Results: This meta-analysis included 6 randomized controlled trials covering 785 participants. The results showed that the combined regimen arm had no significant improvement of PFS (log hazard ratio = -0.228, 95% CI: -0.543 to 0.087, P = 0.157), ORR (odds ratio = 1.147 [95% CI: 0.577, 2.281], P = 0.695), DCR (odds ratio = 1.578 [95% CI: 0.428, 5.821], P = 0.493), and AEs, including fatigue and diarrhea (odds ratio = 0.833 [95% CI: 0.297, 2.333], P = 0.728 for fatigue and odds ratio = 2.268 [95% CI: 0.544, 9.448], P = 0.261 for diarrhea).

Conclusions: Combination therapy may not provide a significant improvement in PFS, ORR, DCR, and incidence of AEs compared with monotherapy in patients with advanced NSCLC with EGFR mutations. Further research is needed to investigate the optimal sequencing of combination therapy in patients with NSCLC with different molecular targets to determine the most effective treatment strategy that can improve outcomes and quality of life for these patients.