Counterpoint: Risk factors, including genetic information, add value in stratifying patients for optimal preventive dental care.
BACKGROUND
There is disagreement as to whether patient stratification by a combination of diabetes, smoking, and genetic test results is useful for informing the frequency of dental prophylaxes.


METHODS
The authors appeal to basic tenets of clinical study design and statistical analysis of clinical investigations, and highlight how secondary ad hoc analyses, such as those of Diehl and colleagues, are frequently underpowered and inconclusive. They also provide evidence from numerous studies supporting the use of genetics to identify risk.


RESULTS
The authors believe the conclusions reached from their original analyses are valid and the analyses of Diehl and colleagues serve to simply reinforce the authors' specific intent of avoiding such underpowered analyses altogether with the Michigan Personalized Prevention Study.


CONCLUSIONS
Until full genome sequencing in many people with highly specified disease phenotypes is feasible, experimental approaches based on biological findings and hypothesis testing should not be summarily discounted.


CONCLUSIONS
Stratification of patients to provide "personalized" treatment remains an important, yet elusive, goal. The current debate serves to highlight the need for large, clinical utility studies that can adequately determine how phenotypic and genotypic data can be best used to improve oral health in the US population.
Thomas M
TM
Braun
Lynn
L
Doucette-Stamm
Gordon W
GW
Duff
Kenneth S
KS
Kornman
William V
WV
Giannobile
D000328:Adult; D003729:Dental Care / Q000706:statistics & numerical data; D003731:Dental Caries / Q000209:etiology / Q000235:genetics / Q000517:prevention & control; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D005820:Genetic Testing; D006801:Humans; D007375:Interleukin-1 / Q000235:genetics; D010518:Periodontitis / Q000209:etiology / Q000235:genetics / Q000517:prevention & control; D011313:Preventive Dentistry / Q000379:methods / Q000706:statistics & numerical data*; D012307:Risk Factors
D007375:Interleukin-1
Comparative effectiveness research; health care delivery; interleukin polymorphisms; oral health; periodontal disease; personalized medicine