Abstract A36: The relationship between modifiable environmental risk factors and colorectal cancer: A systematic review
Bibliographic record
Abstract
Abstract Colorectal cancer is the second leading cause of cancer death in Canada with an estimated 8, 900 deaths per year. The province of Ontario currently has the highest estimated number of deaths from colorectal cancer. Within Ontario, there are prevalent disparities of cancer incidence between communities. Colorectal cancer incidence rates range between >65 new cases per 100, 000 people in communities with higher incidence rates and 45 new cases per 100, 000 people in communities with lower incidence rates. These diverging rates of colorectal cancer have not been studied in relation to modifiable environmental risk factors. As an initial step in assessing these types of risk factors, we are undertaking a systematic review in order to examine current epidemiological evidence on the effects of modifiable environmental risk factors in colorectal cancer incidence. A community based participatory study, as a second step following the systematic review, is currently underway as a case control study among the community groups that present the highest and lowest colorectal cancer incidence rates. The aim of this study is to conduct a synthesis of all primary studies that examine any modifiable environmental risk factors and colorectal cancer using systematic review methodology. We hypothesize that modifiable environmental risk factors are partially responsible for regional colorectal cancer incidence disparities. Seven categories pre-determined for the case control study are also being used for the systematic review as they were found to be the most common modifiable environmental risk factors associated with colorectal cancer in the literature. The categories are air pollution, alcohol, ionizing radiation, metal toxins, occupational exposure, pesticides/organochlorines, and smoking/tobacco. A screening inclusion tool was created in order to identify the articles that would be included in the systematic review. Any original research study, published in English, examining only human participants that discussed any modifiable environmental risk factor and the measurable outcome of colorectal cancer were eligible for inclusion. Studies that examine non human participants, cell lines or DNA components, languages other than English, nutritional components, and examine outcomes other than colorectal cancer were excluded. A comprehensive search of the PubMed database between 1960 and April 2011 was performed using the key words “colorectal neoplasms,” “ethanol,” “alcoholism,” “alcoholic beverages,” “alcoholic drinking,” “smoking,” “tobacco,” “air pollution,” “adverse effects ionizing radiation,” “metals,” “heavy/adverse effects,” “light/adverse effects,” and “occupational exposure,” “pesticides,” and “organochlorine products.” All articles are being reviewed by two researchers utilizing the screening inclusion tool and data extraction form. The articles that pass the inclusion criteria tool are then being categorized further into sub categories in the seven risk factor categories, based on type of study and specific risk factor studied. Initial search yielded 537 citations which are being categorized into the seven different types of risk factors using the inclusion criteria. The strongest evidence will be demonstrated in various categories highlighting characteristics of research methodology, risk factor, and measured outcomes. This evidence will be presented to not only benefit communities with cancer disparities but to benefit the second step of our study regarding a community based case control study. Identification and understanding of the best evidence is imperative to utilize robust methodology and assess research gaps for further community research. Citation Information: Cancer Epidemiol Biomarkers Prev 2011;20(10 Suppl):A36.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".