***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: The propensity score is the probability of treatment assignment conditional on observed baseline characteristics . The propensity score allows one to design and analyze an observational ( nonr and omized ) study so that it mimics some of the particular characteristics of a r and omized controlled trial . In particular , the propensity score is a balancing score : conditional on the propensity score , the distribution of observed baseline covariates will be similar between treated and untreated subjects . I describe 4 different propensity score methods : matching on the propensity score , stratification on the propensity score , inverse probability of treatment weighting using the propensity score  , and covariate adjustment using the propensity score . I describe balance diagnostics for examining whether the propensity score model has been adequately specified . Furthermore , I discuss differences between regression-based methods and propensity score-based methods for the analysis of observational data . I describe different causal average treatment effects and their relationship with propensity score analyses BACKGROUND Controversy exists as to whether low-osmolality radiographic contrast agents , which have less detrimental pharmacological effects but are considerably more expensive than high-osmolality agents , should be used universally or only for selected high-risk patients . METHODS AND RESULTS A r and omized , double-blind study was used to compare the frequency and severity of adverse events in 2245 consecutive patients undergoing diagnostic cardiac angiography . Two thous and one hundred sixty-six patients were successfully r and omized to either iohexol , a low-osmolality contrast agent , or diatrizoate ( as Hypaque 76 ) , a high-osmolality agent . The end point event included clinical ly important adverse events ( which jeopardized the patient or required aggressive treatment ) , contrast agent-related procedure abbreviations , and conversion to open-label contrast agent . Clinical ly important end point events were associated with increased age , New York Heart Association functional class , left ventricular end-diastolic pressure , arteriovenous oxygen difference , severity of coronary artery disease , and history of a previous reaction to contrast agent . End point events were less frequent in patients receiving iohexol ( 2.6 % versus 4.6 % ; adjusted odds ratio , 1.59 ; 95 % confidence interval , 0.97 - 2.60 ; P = .07 ) . The difference in event frequency between iohexol and diatrizoate was confined to the highest-risk quartile of the patient population . An algorithm was developed to classify patients as being at high or low risk for an event based on patient age , New York Heart Association class , history of a prior contrast reaction , and left ventricular end-diastolic pressure . Application of this algorithm for selective use of low-osmolality agents only for high-risk patients to a theoretical population of 1000 patients reduced contrast agent costs 66 % without increasing the frequency of contrast agent-related adverse events . CONCLUSIONS The advantages of low-osmolality contrast agents are clinical ly important in patients with severe heart disease but are not in less ill patients . Universal use of low-osmolality agents for cardiac angiography in an unselected population is not necessary . Appropriately guided selective use of low-osmolality contrast agents is feasible and has the potential to reduce cost substantially without compromising safety or effectiveness The effect of potential risk factors for chronic lymphatic leukaemia was evaluated in a case-referent study encompassing 111 cases and 431 r and omised referents , all alive . Information on exposure was obtained by question naires posted to the subjects . Crude rate ratios were increased for occupational exposure to solvents . DDT , engine exhausts , fresh wood ( lumberjacks , paper pulp workers , and sawmill workers , for example ) and also in farming . Further analysis of the material by means of the Miettinen confounder score technique reduced the number of rate ratios significantly exceeding unity to encompass only occupational exposure to engine exhaust , fresh wood , DDT , and contact with horses The relationship between sociocultural mobility and subsequent  coronary heart disease ( CHD ) and hypertension ( HT ) was studied in a cohort of 13,728 male former Harvard University students examined in 1939 - 1950 . All 13,728 were followed for CHD mortality , while 8852 returned self-administered mail question naires in 1962 or 1966 and in 1972 which queried for doctor-diagnosed myocardial infa rct ion ( MI ) , angina pectoris ( AP ) and HT . For each of 98 cases of fatal CHD , 78 cases of MI and 48 cases of AP , four controls were r and omly selected . One control was selected for each of 319 HT cases . Significant negative associations between father 's occupational status and risk of combined fatal CHD and MI and between geographic mobility and risk of HT were noted in univariate analysis . These associations persisted with stratification by individual confounding factors and by a multivariate confounder-summarizing score . Intergenerational mobility , as indicated by occupational status of the father , was associated with a 1.5 times increased risk of fatal CHD and MI . Intragenerational geographic mobility was associated with a slightly reduced risk of HT The objective of this study was to develop a prospect ively applicable method for classifying comorbid conditions which might alter the risk of mortality for use in longitudinal studies . A weighted index that takes into account the number and the seriousness of comorbid disease was developed in a cohort of 559 medical patients . The 1-yr mortality rates for the different scores were : " 0 " , 12 % ( 181 ) ; " 1 - 2 " , 26 % ( 225 ) ; " 3 - 4 " , 52 % ( 71 ) ; and " greater than or equal to 5 " , 85 % ( 82 ) . The index was tested for its ability to predict risk of death from comorbid disease in the second cohort of 685 patients during a 10-yr follow-up . The percent of patients who died of comorbid disease for the different scores were : " 0 " , 8 % ( 588 ) ; " 1 " , 25 % ( 54 ) ; " 2 " , 48 % ( 25 ) ; " greater than or equal to 3 " , 59 % ( 18 ) . With each increased level of the comorbidity index , there were stepwise increases in the cumulative mortality attributable to comorbid disease ( log rank chi 2 = 165 ; p less than 0.0001 ) . In this longer follow-up , age was also a predictor of mortality ( p less than 0.001 ) . The new index performed similarly to a previous system devised by Kaplan and Feinstein . The method of classifying comorbidity provides a simple , readily applicable and valid method of estimating risk of death from comorbid disease for use in longitudinal studies . Further work in larger population s is still required to refine the approach because the number of patients with any given condition in this study was relatively small Context Few studies have evaluated the relative effectiveness of drug therapies for osteoporosis . Contribution This study compared nonvertebral fractures that occurred within 1 year of initiating osteoporosis pharmacotherapy among 43135 enrollees in 2 statewide pharmaceutical benefit programs . Differences in fracture risk between adults prescribed risedronate or raloxifene and those prescribed  alendronate  were small . Fracture risk seemed to be higher with calcitonin than alendronate . Caution Wide confidence bounds around risk estimates did not rule out potentially important differences between some agents . No adherence data were available , and the ability to account for confounders was limited . Implication There probably is no single clearly superior drug therapy for osteoporosis . The Editors Osteoporosis is characterized by decreased bone mass and deterioration of bone tissue , result ing in reduced bone strength and increased fracture risk ( 1 , 2 ) . Approved therapies for osteoporosis include bisphosphonates , calcitonin , raloxifene , and teriparatide . Findings from r and omized , controlled , head-to-head trials show that women who received alendronate have greater gains in bone mineral density and greater reductions in bone turnover markers within 12 and 24 months of initiation than those who received risedronate ( 3 , 4 ) or raloxifene ( 57 ) . Although bone mineral density is a strong predictor of fracture ( 8) , differences in these surrogate markers may not translate into appreciable differences in fracture risk ( 911 ) . Results from observational studies suggest that risedronate may reduce the risk for nonvertebral fracture ( clavicle , hip , humerus , leg , pelvis , and wrist ) within 12 months more effectively than alendronate or nasal calcitonin ( 12 , 13 ) . To our knowledge , no studies have compared the relative effectiveness of raloxifene versus bisphosphonates or calcitonin in reducing fracture risk . Further comparative effectiveness studies may help to clarify the relative effectiveness of osteoporosis treatments ( 14 ) . We completed a population -based study of new recipients of oral bisphosphonates ( alendronate or risedronate ) , nasal calcitonin , and raloxifene to compare the relative effectiveness of these agents in reducing nonvertebral fracture risk . Methods Study Cohort The study population comprised Medicare beneficiaries enrolled in 2 statewide pharmaceutical benefit plans : the New Jersey Pharmaceutical Assistance to the Aged and Disabled program and the Pennsylvania Pharmaceutical Assistance Contract for the Elderly . These programs provide drug coverage without restriction for low-income residents age 65 years or older with minimal copayment . Our cohort consisted of new recipients ( no use of any of these agents in the previous year ) of oral bisphosphonates ( alendronate , 10 mg or 70 mg , or risedronate , 5 mg or 35 mg ) , nasal calcitonin , or raloxifene  between 1 April 2000 and 30 June 2005 ( Figure 1 ) . To ensure complete plan coverage , study eligibility was limited to patients with 1 or more cl aims in both Medicare and their state pharmaceutical assistance plan in each of the three 6-month intervals preceding the index prescription . We excluded nursing home residents ( for whom prescription data may not be complete ) , patients with a Medicare cl aim for Paget disease ( International Classification of Diseases , Ninth Revision , Clinical Modification code 731.0 ) , and patients with pharmacy cl aims indicating receipt of any bisphosphonate or teriparatide in the year before treatment initiation . Our data included all Medicare beneficiaries from the 2 plans that met eligibility criteria ; we did not do formal sample size calculations . We restricted inclusion to the period when all drugs were available : that is , 1 April 2000 ( risedronate received U.S. Food and Drug Administration approval in April 2000 ) . At the time of analysis , we had complete Medicare data from 1 April 2000 to 31 December 2003 for New Jersey and from 1 April 2000 to 31 December 2005 for Pennsylvania . Figure 1 . Study flow diagram . Osteoporosis drugs were oral bisphosphonates ( alendronate , 10 mg or 70 mg ; risedronate , 5 mg or 35 mg ) , nasal calcitonin , or raloxifene . * May meet > 1 exclusion criterion . Outcomes Our primary outcome of interest was nonvertebral fracture within 12 months of treatment initiation . We defined nonvertebral fracture as a fracture of the hip , humerus , or radius or ulna by using previously vali date d criteria requiring diagnostic and procedural codes from Medicare cl aims ( 15 ) . When medical records are used as the reference st and ard , the estimated sensitivity of each outcome is at least 90 % ( 15 ) . Secondary outcomes included nonvertebral fractures within 6 and 24 months of treatment initiation and hip fracture within 6 , 12 , and 24 months of treatment initiation . Covariates Patient demographic characteristics were determined at treatment initiation and other variables by medical and pharmacy cl aims within the year before treatment initiation . We considered covariates that were plausibly related to our fracture outcomes ( 16 ) : demographic characteristics ( age , sex , race ) , osteoporosis-related factors ( such as diagnosis of osteoporosis , fracture history ) , relevant comorbid conditions ( such as comorbidity score [ 17 , 18 ] ; diabetes mellitus ; history of falls , syncope , and gait abnormalities ; cancer ; rheumatoid arthritis ) , drug use ( such as antiepileptics , -blockers , benzodiazepines , glucocorticoids , hormone therapy , selective serotonin reuptake inhibitors , thiazide diuretics , number of drugs ) , and previous hospitalization . We also included calendar time ( month and year ) of the index prescription to adjust for potential secular trends in prescribing . Appendix Table 1 lists all variables , definitions , and coding . If a record of a specific diagnosis , procedure , or prescription was lacking , patients were coded as not having these characteristics . As a result of this coding rule , there were no participants for whom exposure , confounder , or outcome information was missing . However , race was unknown in 41 patients . These 41 missing data points were recoded as Caucasian . Appendix Table 1 . Definition and Coding of Variables Included in Multinomial Logistic Regression Model Used to Create Propensity Scores Statistical Analysis We calculated fracture rates among recipients of each drug within 6 , 12 , and 24 months of treatment initiation . We used KaplanMeier methods to plot cumulative fracture incidence and Cox proportional hazard models to compare fracture rates between agents . In our primary analysis , we 
    Output:
    
Use of DRS methods has increased yet remains low .