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Prediction Models Help Identify Increased Risk of Gene Mutation Associated with Colorectal Cancer

2006· article· en· W2333395853 on OpenAlexaboutno aff
Heather Lindsey

Bibliographic record

VenueOncology Times · 2006
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsnot available
Fundersnot available
KeywordsColorectal cancerMutationGeneCancerGeneticsMedicineComputational biologyBiologyOncologyBioinformatics

Abstract

fetched live from OpenAlex

Two new prediction models can help identify patients who are likely to have a genetic mutation associated with Lynch Syndrome, the condition that increases the likelihood of developing hereditary nonpolyposis colorectal cancer (Balmaña et al: JAMA 2006;296:1469–1478; and Chen et al: JAMA 2006;296:1479-1487). These models help practitioners identify patients who are most likely to benefit from genetic counseling and testing, explained James M. Ford, MD, the coauthor (with Alice S. Whittemore, PhD) of an accompanying editorial and Associate Professor of Medicine, Pediatrics, and Genetics in the Divisions of Oncology, and Medical Genetics at Stanford University Medical Center and Director of the Clinical Cancer Genetics Program.Figure: James M. Ford, MD, noted in an editorial with Alice S. Whittemore, PhD, that molecular diagnostics and the powerful predictive models reported in the accompanying studies are making genetic testing decisions and management of hereditary cancer syndromes even more complicated, underscoring the necessity for dedicated cancer genetic counselors and cancer risk-assessment clinics that can best use these evolving tools to provide appropriate and evidence-based health care consultation.According to the literature, genetic forms of colon cancer are relatively unusual and apply to about 5% of all individuals diagnosed with the disease, he noted. “The challenge is trying to find who these patients and their families are and providing much more intensive screening. We don't want to apply this type of screening to the general population. We need to pick out those who need it most.” PREMM1,2 Model The study led by Judith Balmaña, MD, found that personal and family history characteristics can accurately predict the outcome of genetic testing in a large population at risk of Lynch syndrome. Dr. Balmaña was formerly with Dana-Farber Cancer Institute and is now at Hospital Vall D'Hebron of Universitat Autonoma of Barcelona in Spain. Lynch syndrome is primarily associated with mutations in the MLH1 and MSH2 genes, and the PREMM1,2 model generates separate probabilities of carrying an MLH1 or MSH2 mutation for each individual in a family, she explained. (PREMM1,2 stands for Prediction of Mutations in MLH1 and MSH2). JAMA 2006;296:1469–1478 and 1479–1487 The researchers obtained data from 1,914 people undergoing genetic testing of MLH1 and MSH2 and created the model, which was developed in an initial group of 898 individuals and then validated in 1,016 patients. Overall, 14.5% of the study individuals were found to have mutations—6.5% of these had mutations in MLH1 and 8.0% carried mutations in MSH2. In the validation cohort, the overall prevalence of mutations was 15.3%. Mutations were particularly prevalent among probands with two or more separate colorectal cancers, endometrial cancer, other Lynch syndrome associated cancers, and multiple diagnoses. The prevalence of mutations in the probands increased with increasing numbers of first-degree relatives with colorectal or endometrial cancer. Probands with mutations had a younger average age at colorectal diagnosis than those who did not have mutations, and the age at diagnosis of colorectal and endometrial cancer was also younger among the relatives of probands with mutations. While other models tend to focus on colorectal and endometrial cancer, the PREMM1,2 model also includes other Lynch syndrome-associated cancers, including ovary, small intestine, pancreas, urinary tract, biliary tract, sebaceous adenomas, and colonic adenomas, Dr. Balmaña said.Figure: Regarding the MMRpro model, Hetal Vig, MS, MGC, CGC, a genetics counselor, noted that other assessment tools such as the Amsterdam Criteria or the Bethesda Guidelines do not necessarily capture the shades of gray that MMRpro does. In addition, MMRpro evaluates a variety of parameters, encompasses pre- and post-genetic testing, detailed family history, and what it means if a test is positive or negative, making it especially useful for the genetics community.One drawback of the model, she noted, is that it does not predict the probability of being an MSH6 mutation carrier, another gene associated with the syndrome, and it doesn't incorporate the impact of the family size or unaffected individuals on the likelihood of being a mutation carrier. Implementing PREMM1,2 in the Clinic In the clinical setting, the model is best suited as a first step in determining whether the person is eligible for further evaluation, said Hetal Vig, MS, MGC, CGC, a cancer genetics counselor at Fox Chase Cancer Center. PREMM1,2 may be most useful for nongenetics professionals or primary care physicians, she noted. “It's a quick look to see if patients should be referred to a genetics counselor for genetic testing.” If a genetic assessment finds that the patient is a mutation carrier or is at high risk for Lynch syndrome, the person should be recommended to have a colonoscopy every one to two years beginning at age 20 to 25, Dr. Balmaña said. Women with or at risk for hereditary nonpolyposis colon cancer should be offered yearly testing for endometrial cancer with endometrial biopsy beginning at age 35, according to American Cancer Society guidelines. Additionally, prophylactic surgery might be an option on an individualized case-by-case basis for patients with Lynch syndrome, Dr. Balmaña said. Further Development She noted that further validation and performance comparisons of PREMM1,2 with other models are needed. In addition, whether clinical decision-making for referral and molecular evaluation of individuals at risk are influenced by the risk estimation obtained with the prediction models should be investigated, she said. MMRpro Model In the other JAMA study, a team led by Sining Chen, PhD, of Johns Hopkins Bloomberg School of Public Health used family medical history and tumor information to develop a Lynch syndrome genetic counseling and risk prediction tool to estimate the probability of carrying a mutation in mismatch repair (MMR) genes MLH1, MSH2, or MSH6, and the probability of developing colorectal or endometrial cancer. The researchers (reporting for the Colon Cancer Family Registry) conducted an external validation of the MMRpro model on 279 individuals from 226 clinic-based families in the United States, Canada, and Australia, by comparing model predictions with results of highly sensitive germline mutation detection techniques. The model predicted the presence of approximately 129 mutations, showing a close correspondence with the observed 121 mutations (ratio of observed to expected results of 0.94). “This results in higher accuracy than existing alternatives and current clinical guidelines,” the authors wrote.Figure: Giovanni Parmigiani, PhD: “MMRpro incorporates explicitly the genetic mechanism by which increased susceptibility to cancer is passed on from one generation to the next, while none of the other models do.”The MMRpro model may have several advantages over other existing models, the senior author, Giovanni Parmigiani, PhD, Professor of Biostatistics, also at Johns Hopkins Bloomberg School of Public Health, noted in an interview. “MMRpro incorporates explicitly the genetic mechanism by which increased susceptibility to cancer is passed on from one generation to the next, while none of the other models do.” Other assessment tools such as the Amsterdam Criteria or Bethesda Guidelines do not necessarily capture the shades of gray that MMRpro does, Ms. Vig explained. MMRpro evaluates a variety of parameters, encompasses pre- and post-genetic testing, detailed family history, and what it means if a test is positive or negative, making it especially useful for the genetics community. Another advantage of MMRpro is that it is built in a modular fashion, allowing researchers to incorporate information from diverse sources, making it more comprehensive, Dr. Parmigiani said. When new studies of risk or prevalence are published, researchers can then easily update the model, and they plan to do so periodically so that patients always have a state-of-the-art tool, he said. Implementing MMRpro in the Clinic Because of the apparent benefits of MMRpro, anyone with a family history of colorectal or endometrial cancer should consider MMRpro testing, Dr. Parmigiani said. “Our data suggest that even a single close relative with early onset colorectal cancer or with endometrial cancer could have their risk increased sufficiently to justify a physician visit and increased screening.” The most common approach to implementing MMRpro in the clinic is to have a genetic counselor or clinician take a family history, determine the risk, and provide the risk evaluation to the patient along with a discussion about inherited susceptibility and screening options. Before testing, patients should understand that the model “cannot foresee the future, but can only help identify groups of people among whom the incidence of cancer events is reliably higher,” Dr. Parmigiani said. Followup care depends on a number of factors, including the level of risk ascertained by the model, he added. “Clinicians can provide advice about this based on the overall clinical profile of the patient and his or her preferences.” Further Development of MMRpro Dr. Parmigiani and his colleagues are actively working on developing detailed recommendations on how to adjust the frequency of screening exams based on the patient's level of risk ascertained by the model. They are also working on incorporating other types of cancer that are associated with the Lynch syndrome into MMRpro. Their most immediate concern, though, he said, is to provide a rigorous comparison of the reliability of the various models that have been recently proposed and to pilot the use of these models in a clinical setting. While this research continues, though, it is crucial to reinforce the message to the public that colorectal cancer is relatively preventable and to encourage oncologists in community settings to educate people with a family history of the disease about the importance of screening, Dr. Parmigiani concluded. PDX Granted Fast Track Designation for T-Cell Lymphoma The FDA has given a Fast Track designation for the antifolate PDX (pralatrexate) for the treatment of patients with T-cell lymphoma. Currently, PDX is the subject of a Phase II, international, multicenter, open-label, single-arm study that will seek to enroll 100 evaluable patients with relapsed or refractory peripheral T-cell lymphoma who have disease progression after at least one prior treatment, according to a news release. The primary endpoint of the study is objective response, and secondary endpoints include duration of response, progression-free survival, and overall survival. PDX is being developed by Allos Therapeutics Inc.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.548

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.280
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations1
Published2006
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