Cancer Patients' Symptom Burden and Health-related Quality of Life (HRQoL) at Tertiary Cancer Center from 2006 to 2013 : A Cross-sectional Study

Background/Aim: To observe changes in symptoms and health-related quality of life (HRQoL) over 7 years among cancer patients at different stages of the disease. Patients and Methods: This prospective cross-sectional study at the Helsinki University Hospital Cancer Center, was carried out in 2006 and repeated in 2013. All participants filled in the EORTC-QLQ-C30 questionnaire. Results: Altogether, 581 patients responded (49% in 2006 and 54% in 2013). The disease was local in 51% and advanced in 49% of patients. The HRQoL was significantly lower, except for emotional and cognitive functions, and the symptom burden more severe in advanced cancer. The most prevalent symptoms were fatigue (93% and 85%; moderate/severe 22% and 9%), pain (65% and 47%; moderate/severe 16% and 5%), and insomnia (64% and 60%; moderate/severe 20 and 21%), respectively. No changes in HRQoL or symptoms were found at 7 years. Conclusion: There is a need for early integrated palliative care to improve HRQoL during cancer treatments.Peer reviewe

Machine-learning-derived classifier predicts absence of persistent pain after breast cancer surgery with high accuracy

Background Prevention of persistent pain following breast cancer surgery, via early identification of patients at high risk, is a clinical need. Supervised machine-learning was used to identify parameters that predict persistence of significant pain. Methods Over 500 demographic, clinical and psychological parameters were acquired up to 6 months after surgery from 1,000 women (aged 28-75 years) who were treated for breast cancer. Pain was assessed using an 11-point numerical rating scale before surgery and at months 1, 6, 12, 24, and 36. The ratings at months 12, 24, and 36 were used to allocate patents to either "persisting pain" or "non-persisting pain" groups. Unsupervised machine learning was applied to map the parameters to these diagnoses. Results A symbolic rule-based classifier tool was created that comprised 21 single or aggregated parameters, including demographic features, psychological and pain-related parameters, forming a questionnaire with "yes/no" items (decision rules). If at least 10 of the 21 rules applied, persisting pain was predicted at a cross-validated accuracy of 86% and a negative predictive value of approximately 95%. Conclusions The present machine-learned analysis showed that, even with a large set of parameters acquired from a large cohort, early identification of these patients is only partly successful. This indicates that more parameters are needed for accurate prediction of persisting pain. However, with the current parameters it is possible, with a certainty of almost 95%, to exclude the possibility of persistent pain developing in a woman being treated for breast cancer.Peer reviewe

A search for modifying genetic factors in CHEK2 : c.1100delC breast cancer patients

The risk of breast cancer associated with CHEK2:c.1100delC is 2-threefold but higher in carriers with a family history of breast cancer than without, suggesting that other genetic loci in combination with CHEK2:c.1100delC confer an increased risk in a polygenic model. Part of the excess familial risk has been associated with common low-penetrance variants. This study aimed to identify genetic loci that modify CHEK2:c.1100delC-associated breast cancer risk by searching for candidate risk alleles that are overrepresented in CHEK2:c.1100delC carriers with breast cancer compared with controls. We performed whole-exome sequencing in 28 breast cancer cases with germline CHEK2:c.1100delC, 28 familial breast cancer cases and 70 controls. Candidate alleles were selected for validation in larger cohorts. One recessive synonymous variant, rs16897117, was suggested, but no overrepresentation of homozygous CHEK2:c.1100delC carriers was found in the following validation. Furthermore, 11 non-synonymous candidate alleles were suggested for further testing, but no significant difference in allele frequency could be detected in the validation in CHEK2:c.1100delC cases compared with familial breast cancer, sporadic breast cancer and controls. With this method, we found no support for a CHEK2:c.1100delC-specific genetic modifier. Further studies of CHEK2:c.1100delC genetic modifiers are warranted to improve risk assessment in clinical practice.Peer reviewe

NTHL1 is a recessive cancer susceptibility gene

Abstract In search of novel breast cancer (BC) risk variants, we performed a whole-exome sequencing and variant analysis of 69 Finnish BC patients as well as analysed loss-of-function variants identified in DNA repair genes in the Finns from the Genome Aggregation Database. Additionally, we carried out a validation study of SERPINA3 c.918-1G>C, recently suggested for BC predisposition. We estimated the frequencies of 41 rare candidate variants in 38 genes by genotyping them in 2482–4101 BC patients and in 1273–3985 controls. We further evaluated all coding variants in the candidate genes in a dataset of 18,786 BC patients and 182,927 controls from FinnGen. None of the variants associated significantly with cancer risk in the primary BC series; however, in the FinnGen data, NTHL1 c.244C>T p.(Gln82Ter) associated with BC with a high risk for homozygous (OR = 44.7 [95% CI 6.90–290], P = 6.7 × 10–5) and a low risk for heterozygous women (OR = 1.39 [1.18–1.64], P = 7.8 × 10–5). Furthermore, the results suggested a high risk of colorectal, urinary tract, and basal-cell skin cancer for homozygous individuals, supporting NTHL1 as a recessive multi-tumour susceptibility gene. No significant association with BC risk was detected for SERPINA3 or any other evaluated gene