Empirical evaluation of language modeling to ascertain cancer outcomes from clinical text reports.

BACKGROUND: Longitudinal data on key cancer outcomes for clinical research, such as response to treatment and disease progression, are not captured in standard cancer registry reporting. Manual extraction of such outcomes from unstructured electronic health records is a slow, resource-intensive process. Natural language processing (NLP) methods can accelerate outcome annotation, but they require substantial labeled data. Transfer learning based on language modeling, particularly using the Transformer architecture, has achieved improvements in NLP performance. However, there has been no systematic evaluation of NLP model training strategies on the extraction of cancer outcomes from unstructured text. RESULTS: We evaluated the performance of nine NLP models at the two tasks of identifying cancer response and cancer progression within imaging reports at a single academic center among patients with non-small cell lung cancer. We trained the classification models under different conditions, including training sample size, classification architecture, and language model pre-training. The training involved a labeled dataset of 14,218 imaging reports for 1112 patients with lung cancer. A subset of models was based on a pre-trained language model, DFCI-ImagingBERT, created by further pre-training a BERT-based model using an unlabeled dataset of 662,579 reports from 27,483 patients with cancer from our center. A classifier based on our DFCI-ImagingBERT, trained on more than 200 patients, achieved the best results in most experiments; however, these results were marginally better than simpler "bag of words" or convolutional neural network models. CONCLUSION: When developing AI models to extract outcomes from imaging reports for clinical cancer research, if computational resources are plentiful but labeled training data are limited, large language models can be used for zero- or few-shot learning to achieve reasonable performance. When computational resources are more limited but labeled training data are readily available, even simple machine learning architectures can achieve good performance for such tasks.

Genetic variation in the body mass index of adult survivors of childhood acute lymphoblastic leukemia: A report from the Childhood Cancer Survivor Study and the St. Jude Lifetime Cohort.

BACKGROUND: Treatment characteristics such as cranial radiation therapy (CRT) do not fully explain adiposity risk in childhood acute lymphoblastic leukemia (ALL) survivors. This study was aimed at characterizing genetic variation related to adult body mass index (BMI) among survivors of childhood ALL. METHODS: Genetic associations of BMI among 1458 adult survivors of childhood ALL (median time from diagnosis, 20 years) were analyzed by multiple approaches. A 2-stage genome-wide association study in the Childhood Cancer Survivor Study (CCSS) and the St. Jude Lifetime Cohort Study (SJLIFE) was performed. BMI was a highly polygenic trait in the general population. Within the known loci, the BMI percent variance explained was estimated, and additive interactions (chi-square test) with CRT in the CCSS were evaluated. The role of DNA methylation in CRT interaction was further evaluated in a subsample of ALL survivors. RESULTS: In a meta-analysis of the CCSS and SJLIFE, 2 novel loci associated with adult BMI among survivors of childhood ALL (LINC00856 rs575792008 and EMR1 rs62123082; PMeta < 5E-8) were identified. It was estimated that the more than 700 known loci explained 6.2% of the variation in adult BMI in childhood ALL survivors. Within the known loci, significant main effects for 23 loci and statistical interactions with CRT at 9 loci (P < 7.0E-5) were further identified. At 2 CRT-interacting loci, DNA methylation patterns may have differed by age. CONCLUSIONS: Adult survivors of childhood ALL have genetic heritability for BMI similar to that observed in the general population. This study provides evidence that treatment with CRT can modify the effect of genetic variants on adult BMI in childhood ALL survivors.

Soft-tissue sarcoma in adolescents and young adults compared with older adults: A report among 5000 patients from the Scandinavian Sarcoma Group Central Register.

BACKGROUND: In recent years, there has been growing awareness of the distinct characteristics of adolescents and young adults (AYA) diagnosed with cancer. Soft-tissue sarcoma (STS) accounts for approximately 1% of all cancers diagnosed in adults and 8% of cancers diagnosed in AYA. To the best of our knowledge, only a few sarcoma registers include data regarding histological subtype, age at diagnosis, and detailed clinical information. Therefore, little is known regarding clinical presentation and outcomes in AYA diagnosed with STS. METHODS: Using the Scandinavian Sarcoma Group Central Register, data were obtained regarding 4977 patients who were diagnosed with STS for the period between 1986 and 2011. AYA (those aged 18-39 years) were compared with older adults (OA; those aged 40-80 years) with respect to clinical presentation, treatment, and outcome. RESULTS: There were 868 AYA and 4109 OA. Overall and by STS subtype, there were significant differences noted between AYA and OA with regard to presentation, treatment, and survival. The distribution of STS subtypes was different between OA and AYA (eg, OA were more likely to be diagnosed with malignant fibrous histiocytoma compared with AYA [34% vs 16%; P < .001]). OA also were more likely to have tumors measuring ≥5 cm (68% vs 56%; P < .001) and a higher malignancy grade (75% vs 67%; P < .001). In the majority of STS subtypes AYA had significantly better overall survival and less disease recurrence compared with OA, but this finding was not true for those with malignant peripheral nerve sheath tumors. CONCLUSIONS: There are several differences between AYA and OA with STS with regard to presentation, treatment, and survival, and such differences must be taken into consideration when designing clinical trials. Additional work also is needed to characterize the potential biological mechanisms underlying these differences.

Survival disparities for second primary malignancies diagnosed among childhood cancer survivors: A population-based assessment.

BACKGROUND: Curative therapy places childhood cancer survivors at increased risk for second primary malignancies (SPMs). However, there have been few population-based attempts to characterize differences between outcomes of SPMs in childhood cancer survivors and outcomes of first primary malignancies (FPMs). METHODS: Clinical and demographic information about childhood cancer survivors who developed SPMs and individuals with comparable FPMs was extracted from the Surveillance, Epidemiology, and End Results program. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated with Cox proportional hazards models comparing the overall survival (OS) of individuals with and without a history of childhood cancer. OS was evaluated both overall and for specific cancers diagnosed in 50 or more childhood cancer survivors. Models accounted for potential confounders, including sex, race, age, treatment decade, histology, and disease stage. RESULTS: Compared with individuals with FPMs (n = 1,332,203), childhood cancer survivors (n = 1409) with an SPM experienced poorer OS (HR, 1.86; 95% CI, 1.72-2.02) after the study had accounted for cancer type, age, sex, race, and decade of diagnosis. A history of childhood cancer remained a poor prognostic factor for all specific cancers evaluated, including breast cancer (HR, 2.07; 95% CI, 1.63-2.62), thyroid cancer (HR, 3.59; 95% CI, 2.08-6.19), acute myeloid leukemia (HR, 2.38; 95% CI, 1.87-3.05), brain cancer (HR, 2.09; 95% CI, 1.72-2.55), melanoma (HR, 2.57; 95% CI, 1.55-4.27), bone cancer (HR, 1.88; 95% CI, 1.37-2.57), and soft-tissue sarcoma (HR, 2.44; 95% CI, 1.78-3.33). CONCLUSIONS: Compared with individuals without a prior cancer diagnosis, survivors of childhood cancer with an SPM experienced inferior outcomes. Survival disparities were observed for the most frequent SPMs diagnosed in childhood cancer survivors.

Pilot study of DNA methylation-derived neutrophil-to-lymphocyte ratio and survival in pediatric medulloblastoma.

INTRODUCTION: Methylation-derived neutrophil-to-lymphocyte ratio (mdNLR) has been identified as a potential prognostic biomarker of outcomes in various cancers. We evaluated the prognostic value of blood-derived mdNLR within a retrospective cohort of pediatric medulloblastoma patients. MATERIALS AND METHODS: DNA methylation was measured in archival peripheral blood samples collected on 56 pediatric medulloblastoma patients. Hazard ratios (HR) and 95% confidence intervals (CI) for the association between mdNLR and survival were evaluated using Cox proportional hazard models. RESULTS: Compared to patients who were alive at last follow-up (n = 43), the mean mdNLR value was slightly higher in deceased patients (n = 13) (12.3 vs. 5.2,P = 0.163). Elevated log-transformed mdNLR was suggestively associated with an increased likelihood of death in unadjusted models (HR=1.43, 95%CI: 0.92-2.22) and significantly associated with mortality in adjusted models (HR=1.61, 95%CI: 1.01-2.58). DISCUSSION: Future work is warranted to investigate the relationship between mdNLR outcomes in specific pediatric medulloblastoma molecular subgroups.

DNA methylation and obesity in survivors of pediatric acute lymphoblastic leukemia: A report from the Childhood Cancer Survivor Study.

Because survivors of pediatric acute lymphoblastic leukemia (ALL) are more likely to be obese than unaffected contemporaries, we compared DNA methylation profiles between normal-weight and obese survivors at adiposity-associated CpG sites previously-reported by epigenome-wide association studies (EWAS) of body mass index (BMI) in the general population. We selected 96 ALL survivors from the Childhood Cancer Survivor Study: 48 obese and 48 normal weight. The Illumina HumanMethylation450 BeadChip was used to compare DNA methylation at 211 loci identified in EWAS of BMI in the general population. Thirty-nine loci were associated (false discovery rate <0.05) with obesity among survivors who only received chemotherapy (n = 49). No loci were significantly associated with obesity among CRT-exposed survivors (n = 47). Our results suggest that previously identified BMI-DNA methylation loci are associated with obesity in ALL survivors who were spared CRT, while no loci were significantly associated with obesity in survivors who received CRT.