Purpose: Adolescent and young adult (AYA) head and neck (H&N) cancer survivors are at risk of long-term complications. A cross-sectional study of survivors recalled for clinical evaluation was performed to evaluate late effects in this population.

Methods: Surviving patients who had been diagnosed with H&N cancer between the ages of 15 and 39 years and treated with radiation therapy (RT) in British Columbia between 1970 and 2010 were invited to participate in this study. Survivors were assessed in consultation by a radiation oncologist for a complete history and physical exam. Comprehensive data collection of subjective and objective late effects of RT and screening investigations were completed.

Results: Of 36 AYA H&N participants, the majority were female (61%), and the most common tumour sites were thyroid (28%), oropharynx (17%), salivary gland (14%) and larynx (14%). Dental extractions post treatment was performed for 33% and dental implants for 17%. The majority (72%) reported xerostomia, 50% had dysphagia to solids and 25% hearing loss. Of the non-thyroid cancer patients who underwent RT to their neck, 45% developed hypothyroidism. There were 28% of participants with asymptomatic carotid stenosis and 27% with thyroid nodules; all were diagnosed after recall screening.

Conclusions: Survivors of AYA H&N cancer treated with RT reported numerous long-term complications. Comprehensive follow-up and screening guidelines should be established for this at-risk population.

Implications For Cancer Survivors: AYA H&N cancer survivors and their primary care practitioners should be educated on screening recommendations and the risk of late effects.

Download full-text PDF

Source
http://dx.doi.org/10.1007/s11764-021-01103-wDOI Listing

Publication Analysis

Top Keywords

cancer survivors
16
h&n cancer
16
late effects
12
aya h&n
12
adolescent young
8
young adult
8
head neck
8
long-term complications
8
study survivors
8
survivors aya
8

Similar Publications

Objective: Addressing the rising cancer rates through timely diagnosis and treatment is crucial. Additionally, cancer survivors need to understand the potential risk of developing secondary cancer (SC), which can be influenced by several factors including treatment modalities, lifestyle choices, and habits such as smoking and alcohol consumption. This study aims to establish a novel relationship using linear regression models between dose and the risk of SC, comparing different prediction methods for lung, colon, and breast cancer.

View Article and Find Full Text PDF

Background: There are limited data on duration of aromatase inhibitor (AI) and cardiovascular disease (CVD) risk in breast cancer (BC) survivors. We examined risk of CVD and mortality associated with duration of AI use in postmenopausal women with early-stage hormone receptor-positive BC.

Methods: Postmenopausal women diagnosed with hormone receptor-positive BC (n = 5,853) who used an AI were included.

View Article and Find Full Text PDF

Background: Due to its rarity, there are very limited data available on the cause of death (COD) and its association with comorbidities in Japanese chronic lymphocytic leukemia (CLL) patients.

Methods: To investigate the prevalence of comorbidities and their impact on cause-specific mortality, we retrospectively reviewed 121 Japanese patients with CLL.

Results: The median age was 69 years, with 47.

View Article and Find Full Text PDF

Penalized landmark supermodels (penLM) for dynamic prediction for time-to-event outcomes in high-dimensional data.

BMC Med Res Methodol

January 2025

Quantitative Sciences Unit, Department of Medicine, Stanford University School of Medicine, 3180 Porter Drive, Office 118, Stanford, CA, 94304, USA.

Background: To effectively monitor long-term outcomes among cancer patients, it is critical to accurately assess patients' dynamic prognosis, which often involves utilizing multiple data sources (e.g., tumor registries, treatment histories, and patient-reported outcomes).

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!