You will be presented with a collection of medical randomized controlled trial (RCT) reports addressing a shared clinical question -- for instance, the efficacy of a medical intervention on a disease or condition. Given the titles and abstracts of these reports, your task is to generate the conclusion of the systematic review article synthesizing the key findings. Your conclusion should be a few sentences long. In your response, include only the conclusion and no other text. The RCT reports are below.



Title 1:
New Users of Metformin Are at Low Risk of Incident Cancer
Abstract 1:
OBJECTIVE The antidiabetic properties of metformin are mediated through its ability to activate the AMP-activated protein kinase ( AMPK ) . Activation of AMPK can suppress tumor formation and inhibit cell growth in addition to lowering blood glucose levels . We tested the hypothesis that metformin reduces the risk of cancer in people with type 2 diabetes . RESEARCH DESIGN AND METHODS In an observational cohort study using record-linkage data bases and based in Tayside , Scotl and , U.K. , we identified people with type 2 diabetes who were new users of metformin in 1994–2003 . We also identified a set of diabetic comparators , individually matched to the metformin users by year of diabetes diagnosis , who had never used metformin . In a survival analysis we calculated hazard ratios for diagnosis of cancer , adjusted for baseline characteristics of the two groups using Cox regression . RESULTS Cancer was diagnosed among 7.3 % of 4,085 metformin users compared with 11.6 % of 4,085 comparators  , with median times to cancer of 3.5 and 2.6 years , respectively ( P < 0.001 ) . The unadjusted hazard ratio ( 95 % CI ) for cancer was 0.46 ( 0.40–0.53 ) . After adjusting for sex , age , BMI , A1C , deprivation , smoking , and other drug use , there was still a significantly reduced risk of cancer associated with metformin : 0.63 ( 0.53–0.75 ) . CONCLUSIONS These results suggest that metformin use may be associated with a reduced risk of cancer . A r and omized trial is needed to assess whether metformin is protective in a population at high risk for cancer


Title 2:
A risk model for prediction of lung cancer.
Abstract 2:
BACKGROUND Reliable risk prediction tools for estimating individual probability of lung cancer have important public health implication s. We constructed and vali date d a comprehensive clinical tool for lung cancer risk prediction by smoking status . METHODS Epidemiologic data from 1851 lung cancer patients and 2001 matched control subjects were r and omly divided into separate training ( 75 % of the data ) and validation ( 25 % of the data ) sets for never , former , and current smokers , and multivariable models were constructed from the training sets . The discriminatory ability of the models was assessed in the validation sets by examining the areas under the receiver operating characteristic curves and with concordance statistics . Absolute 1-year risks of lung cancer were computed using national incidence and mortality data . An ordinal risk index was constructed for each smoking status category by summing the odds ratios from the multivariable regression analyses for each risk factor . RESULTS All variables that had a statistically significant association with lung cancer ( environmental tobacco smoke , family history of cancer , dust exposure , prior respiratory disease , and smoking history variables ) have strong biologically plausible etiologic roles in the disease . The concordance statistics in the validation sets for the never , former , and current smoker models were 0.57 , 0.63 , and 0.58 , respectively . The computed 1-year absolute risk of lung cancer for a hypothetical male current smoker with an estimated relative risk close to 9 was 8.68 % . The ordinal risk index performed well in that true-positive rates in the design ated high-risk categories were 69 % and 70 % for current and former smokers , respectively . CONCLUSIONS If confirmed in other studies , this risk assessment procedure could use easily obtained clinical information to identify individuals who may benefit from increased screening surveillance for lung cancer . Although the concordance statistics were modest , they are consistent with those from other risk prediction models


Title 3:
Variations in lung cancer risk among smokers.
Abstract 3:
BACKGROUND Although there is no proven benefit associated with screening for lung cancer , screening programs are attracting many individuals who perceive themselves to be at high risk due to smoking . We sought to determine whether the risk of lung cancer varies predictably among smokers . METHODS We used data on 18 172 subjects enrolled in the Carotene and Retinol Efficacy Trial (CARET)-a large , r and omized trial of lung cancer prevention-to derive a lung cancer risk prediction model . Model inputs included the subject 's age , sex , asbestos exposure history , and smoking history . We assessed the model 's calibration by comparing predicted and observed rates of lung cancer across risk deciles and vali date d it by assessing the extent to which a model estimated on data from five CARET study sites could predict events in the sixth study site . We then applied the model to evaluate the risk of lung cancer among smokers enrolled in a study of lung cancer screening with computed tomography ( CT ) .  RESULTS The model was internally valid and well calibrated . Ten-year lung cancer risk varied greatly among participants in the CT study , from 15 % for a 68-year-old man who has smoked two packs per day for 50 years and continues to smoke , to 0.8 % for a 51-year-old woman who smoked one pack per day for 28 years before quitting 9 years earlier . Even among the subset of CT study participants who would be eligible for a clinical trial of cancer prevention , risk varied greatly . CONCLUSIONS The risk of lung cancer varies widely among smokers . Accurate risk prediction may help individuals who are contemplating voluntary screening to balance the potential benefits and risks . Risk prediction may also be useful for research ers design ing clinical trials of lung cancer prevention


Title 4:
The Influence of Type 2 Diabetes and Glucose-Lowering Therapies on Cancer Risk in the Taiwanese
Abstract 4:
OBJECTIVE To investigate the association between type 2 diabetes , glucose-lowering therapies ( monotherapy with either metformin , sulphonylurea or insulin ) and cancer risk in Taiwan . METHODS Using Taiwan 's National Health Research Institutes data base of 1,000,000 r and om subjects from 2000 - 2008 , we found 61777 patients with type 2 diabetes ( age ≥20 years ) and 677378 enrollees with no record of diabetes . RESULTS After adjusting for age and sex , we found patients with diabetes to have significantly higher risk of all cancers ( OR : 1.176 ; 95 % CI : 1.149 - 1.204 , P < 0.001 ) . Diabetic patients treated with insulin or sulfonylureas had significantly higher risk of all cancers , compared to those treated with metformin ( OR : 1.583 ; 95 % CI : 1.389 - 1.805 , P < 0.001 and OR : 1.784 ; 95 % CI : 1.406 - 2.262 , P < 0.001 ) . Metformin treatment was associated with a decreased risk of colon and liver cancer compared to sulphonylureas or insulin treatment . Sulfonylureas treatment was associated with an increased risk of breast and lung cancer compared to metformin therapy . CONCLUSIONS Taiwanese with type 2 diabetes are at a high risk of breast , prostate , colon , lung , liver and pancreatic cancer . Those treated with insulin or sulfonylureas monotherapy are more likely to develop colon and liver cancer than those treated with metformin


Title 5:
Lung cancer risk prediction: Prostate, Lung, Colorectal And Ovarian Cancer Screening Trial models and validation.
Abstract 5:
INTRODUCTION Identification of individuals at high risk for lung cancer should be of value to individuals , patients , clinicians , and research ers . Existing prediction models have only modest capabilities to classify persons at risk accurately . METHODS Prospect i ve data from 70 962 control subjects in the Prostate , Lung , Colorectal , and Ovarian Cancer Screening Trial ( PLCO ) were used in models for the general population ( model 1 ) and for a subcohort of ever-smokers ( N = 38 254 ) ( model 2 ) . Both models included age , socioeconomic status ( education ) , body mass index , family history of lung cancer , chronic obstructive pulmonary disease , recent chest x-ray , smoking status ( never , former , or current ) , pack-years smoked , and smoking duration . Model 2 also included  smoking quit-time ( time in years since ever-smokers permanently quit smoking ) . External validation was performed with 44 223 PLCO intervention arm participants who completed a supplemental question naire and were subsequently followed . Known available risk factors were included in logistic regression models . Bootstrap optimism-corrected estimates of predictive performance were calculated ( internal validation ) . Nonlinear relationships for age , pack-years smoked , smoking duration , and quit-time were modeled using restricted cubic splines . All reported P values are two-sided . RESULTS During follow-up ( median 9.2 years ) of the control arm subjects , 1040 lung cancers occurred . During follow-up of the external validation sample ( median 3.0 years ) , 213 lung cancers occurred . For models 1 and 2 , bootstrap optimism-corrected receiver operator characteristic area under the curves were 0.857 and 0.805 , and calibration slopes ( model-predicted probabilities vs observed probabilities ) were 0.987 and 0.979 , respectively . In the external validation sample , models 1 and 2 had area under the curves of 0.841 and 0.784 , respectively . These models had high discrimination in women , men , whites , and nonwhites . CONCLUSION The PLCO lung cancer risk models demonstrate high discrimination and calibration


Title 6:
Antidiabetes drugs correlate with decreased risk of lung cancer: a population-based observation in Taiwan.
Abstract 6:
BACKGROUND The risk of some forms of cancer has been found to be higher in patients with diabetes mellitus ( DM ) than in the general population . The aim of this study was to examine , with sufficient statistical power , the association between DM and lung cancer and the impact of antidiabetes drugs on lung cancer risk in Taiwan . MATERIAL S AND METHODS From a r and omly selected data set of 1 million National Health Insurance ( NHI ) cl aims in Taiwan from 2000 - 2005 , 19,624 cases ( patients ≥ 20 years of age ) of newly diagnosed DM were identified . From the same data set , 78,496 enrollees with no record of DM were selected as controls and were matched in sex and age to the first group . The incidence of newly diagnosed lung cancer was compared between patients with DM and controls for a period of 9 years ( 2000 - 2008 ) . RESULTS The multivariate Cox model analysis showed a slightly increased hazard ratio ( HR ) of 1.05 of lung cancer in patients with DM , but the association was not statistically significant . However the use of antidiabetes drugs , such as metformin , thiazolidinediones , or alpha-glucosidase inhibitors , correlates with a decreased lung cancer risk of 39%-45 % . A significant association was found between lung cancer risk and male sex ( HR , 2.23 ) , pulmonary tuberculosis ( HR , 1.60 ) , chronic obstructive pulmonary disease ( HR , 1.21 ) , and age ( HR , 1.07 ) . CONCLUSION Patients with DM are not at increased risk for the development of lung cancer , but the use of antidiabetes drugs would considerably decrease the risk . In this cohort , male sex , age , pulmonary tuberculosis , and chronic obstructive pulmonary disease were all associated with an increased risk of lung cancer , consistent with findings in the literature and indicative of the validity of our study
Meta- analysis of existing studies does not support a protective or harmful association between  ADMs use and  risk of lung cancer in patients with DM .