Long-term prescribed drug use in stage I-III rectal cancer patients in Sweden, with a focus on bowel-regulating drugs after surgical and oncological treatment.

PURPOSE: To describe long-term prescribed drug use after rectal cancer treatment. METHODS: We identified 12,871 rectal cancer patients without distant metastasis between 2005 and 2016 and 64,341 matched population comparators using CRCBaSe (a Swedish nationwide register linkage of colorectal cancer patients). Mean defined daily doses (DDDs) of drug dispensing during relapse-free follow-up were calculated by Anatomical Therapeutic Chemical drug categories. Incidence rate ratios (IRRs) and 95% confidence intervals (CIs) from negative binomial regression were used to compare drug dispensing between patients and comparators. RESULTS: The overall pattern of drug dispensing was similar among cancer survivors and comparators, although patients had higher mean DDDs of drugs regulating the digestive system. Excess dispensing of drugs for constipation (IRR, 3.35; 95% CI, 3.12-3.61), diarrhea (IRR, 6.43; 95% CI, 5.72-7.22), functional gastrointestinal disorders (IRR, 3.78; 95% CI, 3.15-4.54), and vitamin and mineral supplements (IRR, 1.37; 95% CI, 1.24-1.50) was observed up to 10 years after surgery. Treatment with Hartmann's procedure was associated with higher dispensing rates of digestive drugs compared to surgery with anterior resection and abdominoperineal resection but the association was attributed to higher use of diabetic drugs. Additionally, excess digestive drug dispensing was associated with more advanced cancer stage but not with (chemo)radiotherapy treatment. CONCLUSIONS: Excess drug use after rectal cancer is primarily driven by bowel-regulating drugs and is not modified by surgical or oncological treatment. IMPLICATIONS FOR CANCER SURVIVORS: The excess use of bowel-regulating drugs after rectal cancer indicated long-standing postsurgical gastrointestinal morbidity and need of prophylaxis. Reassuringly, no excess use of other drug classes was noted long term.

Optimizing Outcome Prediction in Diffuse Large B-Cell Lymphoma by Use of Machine Learning and Nationwide Lymphoma Registries: A Nordic Lymphoma Group Study.

PURPOSE: Prognostic models for diffuse large B-cell lymphoma (DLBCL), such as the International Prognostic Index (IPI) are widely used in clinical practice. The models are typically developed with simplicity in mind and thus do not exploit the full potential of detailed clinical data. This study investigated whether nationwide lymphoma registries containing clinical data and machine learning techniques could prove to be useful for building modern prognostic tools. PATIENTS AND METHODS: This study was based on nationwide lymphoma registries from Denmark and Sweden, which include large amounts of clinicopathologic data. Using the Danish DLBCL cohort, a stacking approach was used to build a new prognostic model that leverages the strengths of different survival models. To compare the performance of the stacking approach with established prognostic models, cross-validation was used to estimate the concordance index (C-index), time-varying area under the curve, and integrated Brier score. Finally, the generalizability was tested by applying the new model to the Swedish cohort. RESULTS: In total, 2,759 and 2,414 patients were included from the Danish and Swedish cohorts, respectively. In the Danish cohort, the stacking approach led to the lowest integrated Brier score, indicating that the survival curves obtained from the stacking model fitted the observed survival the best. The C-index and time-varying area under the curve indicated that the stacked model (C-index: Denmark [DK], 0.756; Sweden [SE], 0.744) had good discriminative capabilities compared with the other considered prognostic models (IPI: DK, 0.662; SE, 0.661; and National Comprehensive Cancer Network-IPI: DK, 0.681; SE, 0.681). Furthermore, these results were reproducible in the independent Swedish cohort. CONCLUSION: A new prognostic model based on machine learning techniques was developed and was shown to significantly outperform established prognostic indices for DLBCL. The model is available at https://lymphomapredictor.org .

Medical history, lifestyle, family history, and occupational risk factors for mantle cell lymphoma: the InterLymph Non-Hodgkin Lymphoma Subtypes Project.

BACKGROUND: The etiology of mantle cell lymphoma (MCL), a distinctive subtype accounting for 2%-10% of all non-Hodgkin lymphoma, is not known. METHODS: We investigated associations with self-reported medical history, lifestyle, family history, and occupational risk factors in a pooled analysis of 557 patients with MCL and 13766 controls from 13 case-control studies in Europe, North America, and Australia. Odds ratios (ORs) and 95% confidence intervals (CIs) associated with each exposure were examined using multivariate logistic regression models. RESULTS: The median age of the MCL patients was 62 years and 76% were men. Risk of MCL was inversely associated with history of hay fever (OR = 0.63, 95% CI = 0.48 to 0.82), and the association was independent of other atopic diseases and allergies. A hematological malignancy among first-degree relatives was associated with a twofold increased risk of MCL (OR = 1.99, 95% CI = 1.39 to 2.84), which was stronger in men (OR = 2.21, 95% CI = 1.44 to 3.38) than women (OR = 1.61, 95% CI = 0.82 to 3.19). A modestly increased risk of MCL was also observed in association with ever having lived on a farm (OR = 1.40, 95% CI = 1.03 to 1.90). Unlike some other non-Hodgkin lymphoma subtypes, MCL risk was not statistically significantly associated with autoimmune disorders, tobacco smoking, alcohol intake, body mass index, or ultraviolet radiation. CONCLUSIONS: The novel observations of a possible role for atopy and allergy and farm life in risk of MCL, together with confirmatory evidence of a familial link, suggest a multifactorial etiology of immune-related environmental exposures and genetic susceptibility. These findings provide guidance for future research in MCL etiology.