Pragmatic considerations for negative control outcome studies to guide non-randomized comparative analyses: A narrative review.

PURPOSE: This narrative review describes the application of negative control outcome (NCO) methods to assess potential bias due to unmeasured or mismeasured confounders in non-randomized comparisons of drug effectiveness and safety. An NCO is assumed to have no causal relationship with a treatment under study while subject to the same confounding structure as the treatment and outcome of interest; an association between treatment and NCO then reflects the potential for uncontrolled confounding between treatment and outcome. METHODS: We focus on two recently completed NCO studies that assessed the comparability of outcome risk for patients initiating different osteoporosis medications and lipid-lowering therapies, illustrating several ways in which confounding may result. In these studies, NCO methods were implemented in claims-based data sources, with the results used to guide the decision to proceed with comparative effectiveness or safety analyses. RESULTS: Based on this research, we provide recommendations for future NCO studies, including considerations for the identification of confounding mechanisms in the target patient population, the selection of NCOs expected to satisfy required assumptions, the interpretation of NCO effect estimates, and the mitigation of uncontrolled confounding detected in NCO analyses. We propose the use of NCO studies prior to initiating comparative effectiveness or safety research, providing information on the potential presence of uncontrolled confounding in those comparative analyses. CONCLUSIONS: Given the increasing use of non-randomized designs for regulatory decision-making, the application of NCO methods will strengthen study design, analysis, and interpretation of real-world data and the credibility of the resulting real-world evidence.

Trends in characteristics and outcomes among US adults hospitalised with COVID-19 throughout 2020: an observational cohort study.

OBJECTIVES: To examine the temporal patterns of patient characteristics, treatments used and outcomes associated with COVID-19 in patients who were hospitalised for the disease between January and 15 November 2020. DESIGN: Observational cohort study. SETTING: COVID-19 subset of the Optum deidentified electronic health records, including more than 1.8 million patients from across the USA. PARTICIPANTS: There were 51 510 hospitalised patients who met the COVID-19 definition, with 37 617 in the laboratory positive cohort and 13 893 in the clinical cohort. PRIMARY AND SECONDARY OUTCOME MEASURES: Incident acute clinical outcomes, including in-hospital all-cause mortality. RESULTS: Respectively, 48% and 49% of the laboratory positive and clinical cohorts were women. The 50- 65 age group was the median age group for both cohorts. The use of antivirals and dexamethasone increased over time, fivefold and twofold, respectively, while the use of hydroxychloroquine declined by 98%. Among adult patients in the laboratory positive cohort, absolute age/sex standardised incidence proportion for in-hospital death changed by -0.036 per month (95% CI -0.042 to -0.031) from March to June 2020, but remained fairly flat from June to November, 2020 (0.001 (95% CI -0.001 to 0.003), 17.5% (660 deaths /3986 persons) in March and 10.2% (580/5137) in October); in the clinical cohort, the corresponding changes were -0.024 (95% CI -0.032 to -0.015) and 0.011 (95% CI 0.007 0.014), respectively (14.8% (175/1252) in March, 15.3% (189/1203) in October). Declines in the cumulative incidence of most acute clinical outcomes were observed in the laboratory positive cohort, but not for the clinical cohort. CONCLUSION: The incidence of adverse clinical outcomes remains high among COVID-19 patients with clinical diagnosis only. Patients with COVID-19 entering the hospital are at elevated risk of adverse outcomes.

A Novel Case Study of the Use of Real-World Evidence to Support the Registration of an Osteoporosis Product in China.

On June 23, 2020, Prolia® (denosumab) was approved by the National Medical Products Administration (NMPA) in the People's Republic of China as the first monoclonal antibody for the treatment of postmenopausal women with osteoporosis at high risk of fractures. Its brand name in Chinese is , a transliteration from the English name "Prolia", which has an implied meaning of "to give strength to everyone"- a suitable name for a potent anti-resorptive therapy. The approval was supported by a novel marketing authorization application (MAA) that included data from Prolia's global clinical trial program establishing favorable efficacy and safety, augmented by results from a real-world evidence (RWE) study confirming the effectiveness and safety of Prolia in clinical practice within Taiwan and Hong Kong. Key constructs for this registration-quality RWE study included the fit-for-purpose assessment of data quality, methodology and quantitative assessment of potential biases, good practices of study conduct, and reproducibility of results. Using data from clinical practice in Taiwan and Hong Kong to evaluate the benefits versus risks of Prolia treatment in ethnic Chinese women with postmenopausal osteoporosis, the RWE study results for effectiveness were comparable to efficacy demonstrated in the global clinical trial program and results for safety were consistent with the incidence observed in global post-marketing safety studies. While RWE is often used to monitor postmarket safety of drug products, support health insurance coverage decisions, and inform clinicians on real-world use of medicines, it has not been widely used to support regulatory approval for new medicines in lieu of clinical bridging studies in countries where such studies are required. Well-conducted registrational RWE studies can play a pivotal role in complementing the totality of evidence presented in an MAA. The benefits of such an approach include avoiding the collection of additional placebo-controlled trial data in populations where adequate ethnic characterization of efficacy, effectiveness, and safety may already exist from postmarketing sources, and accelerate access for patients to innovative medicines in important regions. Here, we describe a regulatory case study of a novel MAA incorporating RWE that provided important evidence to confirm the benefit:risk of a new drug and facilitated a label expansion to a new patient population.

Machine learning applications for therapeutic tasks with genomics data.

Thanks to the increasing availability of genomics and other biomedical data, many machine learning algorithms have been proposed for a wide range of therapeutic discovery and development tasks. In this survey, we review the literature on machine learning applications for genomics through the lens of therapeutic development. We investigate the interplay among genomics, compounds, proteins, electronic health records, cellular images, and clinical texts. We identify 22 machine learning in genomics applications that span the whole therapeutics pipeline, from discovering novel targets, personalizing medicine, developing gene-editing tools, all the way to facilitating clinical trials and post-market studies. We also pinpoint seven key challenges in this field with potentials for expansion and impact. This survey examines recent research at the intersection of machine learning, genomics, and therapeutic development.

Characteristics and outcomes of hospitalised adults with COVID-19 in a Global Health Research Network: a cohort study.

OBJECTIVE: To examine age, gender, and temporal differences in baseline characteristics and clinical outcomes of adult patients hospitalised with COVID-19. DESIGN: A cohort study using deidentified electronic medical records from a Global Research Network. SETTING/PARTICIPANTS: 67 456 adult patients hospitalised with COVID-19 from the USA; 7306 from Europe, Latin America and Asia-Pacific between February 2020 and January 2021. RESULTS: In the US cohort, compared with patients 18-34 years old, patients ≥65 had a greater risk of intensive care unit (ICU) admission (adjusted HR (aHR) 1.73, 95% CI 1.58 to 1.90), acute respiratory distress syndrome(ARDS)/respiratory failure (aHR 1.86, 95% CI 1.76 to 1.96), invasive mechanical ventilation (IMV, aHR 1.93, 95% CI, 1.73 to 2.15), and all-cause mortality (aHR 5.6, 95% CI 4.36 to 7.18). Men appeared to be at a greater risk for ICU admission (aHR 1.34, 95% CI 1.29 to 1.39), ARDS/respiratory failure (aHR 1.24, 95% CI1.21 to 1.27), IMV (aHR 1.38, 95% CI 1.32 to 1.45), and all-cause mortality (aHR 1.16, 95% CI 1.08 to 1.24) compared with women. Moreover, we observed a greater risk of adverse outcomes during the early pandemic (ie, February-April 2020) compared with later periods. In the ex-US cohort, the age and gender trends were similar; for the temporal trend, the highest proportion of patients with all-cause mortality were also in February-April 2020; however, the highest percentages of patients with IMV and ARDS/respiratory failure were in August-October 2020 followed by February-April 2020. CONCLUSIONS: This study provided valuable information on the temporal trends of characteristics and outcomes of hospitalised adult COVID-19 patients in both USA and ex-USA. It also described the population at a potentially greater risk for worse clinical outcomes by identifying the age and gender differences. Together, the information could inform the prevention and treatment strategies of COVID-19. Furthermore, it can be used to raise public awareness of COVID-19's impact on vulnerable populations.

Real-world evidence to support regulatory decision making: New or expanded medical product indications.

There is increasing interest in utilizing real-world data (RWD) to produce real-world evidence (RWE) on the benefits and risks of medical products that could support regulatory approval decisions. The field of pharmacoepidemiology has a long history of focusing on data and evidence that would now be termed "real-world," including evidence from healthcare claims, registries, and electronic health records. However, several emerging trends over the past decade are converging to support the use of these and other RWD sources for approval decisions, and there are several recent examples and ongoing research that demonstrate how RWE may be used to support regulatory approval of new or expanded indications. The goal of this article is to review the current landscape and future directions of the use of RWE in this context. This manuscript is endorsed by the International Society for Pharmacoepidemiology (ISPE).

Real-world evidence to support regulatory decision-making for medicines: Considerations for external control arms.

Randomized clinical trials (RCTs) are the gold standard in producing clinical evidence of efficacy and safety of medical interventions. More recently, a new paradigm is emerging-specifically within the context of preauthorization regulatory decision-making-for some novel uses of real-world evidence (RWE) from a variety of real-world data (RWD) sources to answer certain clinical questions. Traditionally reserved for rare diseases and other special circumstances, external controls (eg, historical controls) are recognized as a possible type of control arm for single-arm trials. However, creating and analyzing an external control arm using RWD can be challenging since design and analytics may not fully control for all systematic differences (biases). Nonetheless, certain biases can be attenuated using appropriate design and analytical approaches. The main objective of this paper is to improve the scientific rigor in the generation of external control arms using RWD. Here we (a) discuss the rationale and regulatory circumstances appropriate for external control arms, (b) define different types of external control arms, and (c) describe study design elements and approaches to mitigate certain biases in external control arms. This manuscript received endorsement from the International Society for Pharmacoepidemiology (ISPE).

Predictive values of diagnostic codes for identifying serious hypocalcemia and dermatologic adverse events among women with postmenopausal osteoporosis in a commercial health plan database.

BACKGROUND: Post-marketing safety studies of medicines often rely on administrative claims databases to identify adverse outcomes following drug exposure. Valid ascertainment of outcomes is essential for accurate results. We aim to quantify the validity of diagnostic codes for serious hypocalcemia and dermatologic adverse events from insurance claims data among women with postmenopausal osteoporosis (PMO). METHODS: We identified potential cases of serious hypocalcemia and dermatologic events through ICD-9 diagnosis codes among women with PMO within claims from a large US healthcare insurer (June 2005-May 2010). A physician adjudicated potential hypocalcemic and dermatologic events identified from the primary position on emergency department (ED) or inpatient claims through medical record review. Positive predictive values (PPVs) and 95% confidence intervals (CIs) quantified the fraction of potential cases that were confirmed. RESULTS: Among 165,729 patients with PMO, medical charts were obtained for 40 of 55 (73%) potential hypocalcemia cases; 16 were confirmed (PPV 40%, 95% CI 25-57%). The PPV was higher for ED than inpatient claims (82 vs. 24%). Among 265 potential dermatologic events (primarily urticaria or rash), we obtained 184 (69%) charts and confirmed 128 (PPV 70%, 95% CI 62-76%). The PPV was higher for ED than inpatient claims (77 vs. 39%). CONCLUSION: Diagnostic codes for hypocalcemia and dermatologic events may be sufficient to identify events giving rise to emergency care, but are less accurate for identifying events within hospitalizations.

Changes in the use of erythropoiesis-stimulating agents (ESAs) and red blood cell transfusion in patients with cancer amidst regulatory and reimbursement changes.

PURPOSE: Evaluate changes in use of erythropoiesis-stimulating agents (ESAs) and red blood cell transfusion in cancer patients receiving myelosuppressive chemotherapy following regulatory and reimbursement actions. METHODS: Calendar year patient cohorts (2005-2013) with breast, colorectal, lung, multiple myeloma, non-Hodgkin lymphoma, ovarian, or prostate cancer and receiving myelosuppressive chemotherapy were identified within the Marketscan database. Incidence of ESA treatment and transfusion were estimated in each year, as was median number of ESA administrations. Clinical characteristics associated with ESA administration and transfusions were evaluated by using multivariable logistic regression. Additionally, annual new ESA user cohorts within the Oncology Services Comprehensive Electronic Records database (2011-2014) were examined to assess hemoglobin levels at ESA initiation. RESULTS: Across all tumor types, ESA use decreased substantially (breast cancer: 53.7 to 3.2%; lung cancer: 66.0 to 13.3%, non-Hodgkin lymphoma: 39.8 to 3.8%), transfusion use increased (2 to 5.5%, 5.5 to 18.2%, and 4.5 to 9.1%, respectively), and median number of ESA administrations declined. Across all tumor types, proportion of patients initiating an ESA with hemoglobin >10 g/dL was <10% from 2011 onward. In recent years, cancer patients who are older, female, and have chronic kidney disease or moderate or severe liver disease were most likely to receive ESAs. CONCLUSION: Subsequent to important regulatory and reimbursement ESA-related actions, total ESA exposure among cancer patients receiving myelosuppressive chemotherapy declined substantially. Today, fewer patients receive ESA therapy, and among those treated, more are initiated at hemoglobin levels <10 g/dL and are exposed for a shorter duration, consistent with current product labeling.

The impact of persistence with bisphosphonates on health resource utilization and fracture risk in the UK: a study of patient records from the UK Clinical Practice Research Datalink.

RATIONALE, AIMS AND OBJECTIVES: Clinical trial data suggest that patients who have received bisphosphonates continue to benefit from them after discontinuation. However, data from real-world clinical practice are inconclusive. We assessed the impact of persistence and discontinuation on health resource utilization (HRU) and fracture rate in women who were prescribed oral bisphosphonates. METHOD: The study used data from the UK Clinical Practice Research Datalink. Women aged 50 years or older with a first prescription of oral bisphosphonate therapy between January 2000 and December 2007 were included. Multivariate modelling compared rate ratios for fracture and HRU between patients who had discontinued medication (shorter persistence group) and patients who took their medication for longer (longer persistence group). The interactions of elapsed time (measured as 6-month intervals) with HRU and with fracture rate for all patients within paired groups were also assessed. RESULTS: Overall, 36 320 patients were included. Pairwise comparisons showed that HRU and fracture rates were lower in longer persistence groups than in shorter persistence groups. Analysis by 6-month interval showed that, across all patients in persistence group pairs, HRU significantly increased for each additional 6 months elapsed; trends towards increased risk of fracture were also seen. CONCLUSION: In contrast to results from clinical trials, in this patient population the protective effect of oral bisphosphonates after discontinuation was not sufficient to reduce HRU and fracture rates to the levels that would be seen if patients had continued on therapy. Reducing the rate of treatment discontinuation may decrease the burden that osteoporosis places on both patients and health care systems.

Development and evaluation of an algorithm to identify users of Prolia(®) during the early postmarketing period using health insurance claims data.

PURPOSE: The goal of this study is to develop and validate an algorithm to identify Prolia(®) users within a health insurance claims database. METHODS: Patients with a denosumab-specific or nonspecific administration claim during the early period of Prolia availability in the USA (June 1, 2010 to March 31, 2012) were classified as definite, probable, possible, and nonusers of Prolia using an algorithm consisting of nine different components based on claims patterns consistent with Prolia use. Medical record review confirmed a sample of definite, probable, and possible users and the positive predictive value (PPV) was estimated. RESULTS: The PPV of the claims-based algorithm components varied (17.8-95.8%). Requiring claims for a bone or cartilage disorder or osteoporotic fracture after excluding claims for cancer prior to a denosumab-specific administration code gave the highest PPV (95.8%), followed by requiring a Prolia National Drug Code on the same claim as a denosumab-specific or nonspecific administration code (88.2%). Among the 87 confirmed Prolia users, osteoporosis diagnoses were seen more frequently in the medical record than in claims (83% vs 62%). CONCLUSIONS: Prolia users are most accurately identified with administration code claims in conjunction with claims for Prolia National Drug Code and bone disorder treatment and diagnosis codes. Osteoporosis diagnoses may be under-recorded in claims data. The algorithm may require reassessment as uptake for more recently approved indications increases.

Changing patterns of use of osteoporosis medications in the years after launch: implications for comparative effectiveness research.

PURPOSE: Newly marketed medications may be used selectively in patients with more severe disease. Changes in patterns of use following a drug's introduction to the market can greatly influence results from non-experimental comparative effectiveness research. We sought to explore this issue by characterizing trends in oral and injectable prescription drug claims for the prevention and treatment of osteoporosis. METHODS: We examined a post-menopausal population of women age 55 years and older in the Truven Health Analytics MarketScan® Databases. We used propensity score (PS) methods to describe how predictors of new users of oral and injectable osteoporosis medications change over time. RESULTS: We found that injectable osteoporosis medications tended to be used more selectively in the higher risk patients shortly after launch. Over time, they appeared to be used increasingly in lower risk patients. CONCLUSION: If disease severity is incompletely captured in the data, comparative effectiveness of novel osteoporosis medications may be difficult to accurately estimate, particularly when medications are new to market.

Discontinuation and reinitiation patterns of osteoporosis treatment among commercially insured postmenopausal women.

OBJECTIVE: Poor adherence to chronic medications is common and compromises medication effectiveness. We sought to describe longitudinal patterns of osteoporosis medication use. STUDY DESIGN: This was a retrospective observational cohort study using 2005-2009 data from a large, commercially insured population. METHODS: Patients were women aged ≥55 years initiating osteoporosis therapy who had a ≥12-month (baseline) period with no osteoporosis therapy claims preceding initiation, and ≥24 months follow-up after therapy initiation. Discontinuation was defined as a gap >60 days (varied in sensitivity analyses) in prescription claims. Reinitiation was defined as a prescription claim for the same or different osteoporosis therapy following the therapy gap. Discontinuation and reinitiation patterns were described using Kaplan-Meier analysis. Multivariable Cox regression assessed the impact of baseline factors on reinitiation. RESULTS: Of the 92,839 patients, 45%, 58%, and 70% discontinued therapy at 6, 12, and 24 months, respectively, following initiation. Of the discontinuers, 46% reinitiated therapy, with the majority doing so within 6 months of discontinuation. Women were less likely to reinitiate therapy if they were older (P < 0.0001) or were hospitalized during baseline (P = 0.0007). Women who discontinued treatment early (<6 months) following initiation were less likely to reinitiate (P < 0.0001) and remained on therapy for shorter periods following reinitiation. Depending on the available observation time, the median time on therapy following reinitiation was 58-193 days. Study findings did not change appreciably in sensitivity analyses. CONCLUSION: Many patients stop and restart treatment for osteoporosis. A better understanding of determinants of treatment stopping and restarting could inform adherence improvement efforts.

Validity of an algorithm to identify osteonecrosis of the jaw in women with postmenopausal osteoporosis in the Danish National Registry of Patients.

BACKGROUND: Osteonecrosis of the jaw (ONJ) is an adverse effect of drugs that suppress bone turnover - for example, drugs used for the treatment of postmenopausal osteoporosis. The Danish National Registry of Patients (DNRP) is potentially valuable for monitoring ONJ and its prognosis; however, no specific code for ONJ exists in the International Classification of Diseases 10th revision (ICD-10), which is currently used in Denmark. Our aim was to estimate the positive predictive value (PPV) of an algorithm to capture ONJ cases in the DNRP among women with postmenopausal osteoporosis. METHODS: We conducted this cross-sectional validation study in the Central and North Denmark Regions, with approximately 1.8 million inhabitants. In total, 54,956 women with postmenopausal osteoporosis were identified from June 1, 2005 through May 31, 2010. To identify women potentially suffering from ONJ, we applied an algorithm based on ICD-10 codes in the DNRP originating from hospital-based departments of oral and maxillofacial surgery (DOMS). ONJ was adjudicated by chart review and defined by the presence of exposed maxillofacial bone for 8 weeks or more, in the absence of recorded history of craniofacial radiation therapy. We estimated the PPV for the overall algorithm and for each separate ICD-10 code used in the algorithm. RESULTS: Charts were obtained and reviewed for all 60 women with an ICD-10 code potentially representing ONJ. Nineteen potential ONJ cases were confirmed, corresponding to an overall PPV of 32% (95% confidence interval: 20%-45%). CONCLUSION: Among women with postmenopausal osteoporosis, only about one-third of the potential ONJ cases identified by our ICD-10 based algorithm were confirmed by medical chart review, despite the restriction to patients treated at DOMS. To capture true ONJ cases among women with postmenopausal osteoporosis, alternative approaches are needed.

Design and methods of a postmarketing pharmacoepidemiology study assessing long-term safety of Prolia® (denosumab) for the treatment of postmenopausal osteoporosis.

PURPOSE: To describe the rationale and methods for a prospective, open-cohort study assessing the long-term safety of Prolia(®) for treatment of postmenopausal osteoporosis (PMO) in postmarketing settings. METHODS: Data will be derived from United States Medicare, United Healthcare, and Nordic (Denmark, Sweden, Norway) national registries. Observation will begin on the date of first Prolia(®) regulatory approval (May 26, 2010) and continue for 10 years. Women with PMO will be identified by postmenopausal age, osteoporosis diagnosis, osteoporotic fracture, or osteoporosis treatment. Exposure to Prolia(®) and bisphosphonates will be updated during follow-up; exposure cohorts will be defined based on patient-years during which patients are on- or post-treatment. Nine adverse events (AEs) will be assessed based on diagnosis codes: osteonecrosis of the jaw (ONJ), atypical femoral fracture (AFF), fracture healing complications, hypocalcemia, infection, dermatologic AEs, acute pancreatitis, hypersensitivity, and new primary malignancy. Medical review will confirm selected potential cases of ONJ and AFF. Incidence rates (IRs) of AEs will be described overall and for exposure cohorts; multivariate Cox proportional hazard regression models will compare IRs of AEs across exposure cohorts. Utilization patterns of Prolia(®) for approved, and unapproved indications will be described. CONCLUSION: This study is based on comprehensive preliminary research and considers methodological challenges specific to the study population. The integrated data systems used in this regulatory committed program can serve as a powerful data resource to assess diverse and rare AEs over time.

Completeness of prescription information in US commercial claims databases.

PURPOSE: Pharmacy commercial claims databases are widely used for pharmacoepidemiologic research. However, concerns have been raised that these databases may not fully capture claims for generic medications as a result of patients filling outside the context of their insurance. This has implications for many research activities and quality improvement programs. We sought to estimate the percentage of missing prescriptions in US commercial claims data using a novel design. METHODS: Using a large US commercial insurance database, we examined the completeness of warfarin prescription claims among patients with atrial fibrillation receiving regular medical follow-up and testing to manage warfarin dosing. We examined 14 different 6-month cross sections. Each cross section was treated independently to identify patients with at least two outpatient diagnoses of atrial fibrillation, two international normalized ratio tests, and one pharmacy claim. Trends in the percentage of patients with prescription claims for generic and branded warfarin were compared by year and 6-month periods using chi-square tests and generalized linear models adjusting for patient characteristics. RESULTS: Out of 111 170 patients, the percentage of patients with any warfarin drug decreased slightly from 91.7% (95% CI: 91.0, 92.4) in early 2003 to 87.1% (95% CI: 86.7-87.6) in late 2009 (χ(2) = 93.8, p < 0.0001). Over the same interval, the proportion of patients with generic warfarin exposure appearing increased significantly, whereas the proportion of patients with branded warfarin exposure decreased significantly. CONCLUSIONS: Our study supports the possibility that some prescriptions may not be captured in US commercial insurance databases.

Accuracy of ICD-9 codes to identify nonunion and malunion and developing algorithms to improve case-finding of nonunion and malunion.

OBJECTIVE: To evaluate the accuracy of using ICD-9 codes to identify nonunions (NU) and malunions (MU) among adults with a prior fracture code and to explore case-finding algorithms. STUDY DESIGN: Medical chart review of potential NU (N=300) and MU (N=288) cases. True NU cases had evidence of NU and no evidence of MU in the chart (and vice versa for MUs) or were confirmed by the study clinician. Positive predictive values (PPV) were calculated for ICD-9 codes. Case-finding algorithms were developed by a classification and regression tree analysis using additional automated data, and these algorithms were compared to true case status. SETTING: Group Health Cooperative. RESULTS: Compared to true cases as determined from chart review, the PPV of ICD-9 codes for NU and MU were 89% (95% CI, 85-92%) and 47% (95% CI, 41-53%), respectively. A higher proportion of true cases (NU: 95%; 95% CI, 90-98%; MU: 56%; 95% CI, 47-66%) were found among subjects with 1+ additional codes occurring in the 12months following the initial code. There was no case-finding algorithm for NU developed given the high PPV of ICD-9 codes. For MU, the best case-finding algorithm classified people as an MU case if they had a fracture in the forearm, hand, or skull and had no visit with an NU diagnosis code in the 12-month post MU diagnosis. PPV for this MU case-finding algorithm increased to 84%. CONCLUSIONS: Identifying NUs with its ICD-9 code is reasonable. Identifying MUs with automated data can be improved by using a case-finding algorithm that uses additional information. Further validation of the MU algorithms in different populations is needed, as well as exploration of its performance in a larger sample.

Patient-related risk factors for fracture-healing complications in the United Kingdom General Practice Research Database.

BACKGROUND AND PURPOSE: A variety of risk factors have been hypothesized to contribute to the development of fracture-healing complications; however, population-based estimates of the strength of these risk factors are limited. In this case-control study, we evaluated patient-related risk factors for fracture-healing complications. METHODS: Using the United Kingdom General Practice Research Database, we identified patients with a fracture-healing complication (delayed union, nonunion, or malunion) between 1988 and 2008. 4 controls (i.e. patients with normal healing) were matched to each case on general practice, fracture site, fracture date, and length of history in the database. We used conditional logistic regression to estimate odds ratios (ORs) of various risk factors, including demographics, comorbidities, and medication use. RESULTS: Diabetes and use of non-steroidal anti-inflammatory drugs (NSAIDs) within 12 months before the initial fracture were associated with a higher odds of a fracture-healing complication (type-I diabetes: adjusted OR = 2.3, 95% CI: 1.3-3.8; type-II diabetes: adjusted OR = 2.3, CI: 1.4-3.7; NSAIDs: adjusted OR = 2.6, CI: 2.1-3.2). Patients who had a motor vehicle accident recorded within 1 month before their initial fracture were also at increased odds of a fracture-healing complication (adjusted OR = 2.6, CI: 1.2-5.4). INTERPRETATION: Diabetes, NSAID use, and a recent motor vehicle accident were most consistently associated with an increased risk of a fracture-healing complication, regardless of fracture site or specific fracture-healing complication. This analysis suggests that certain patient-related characteristics influence the development of fracture-healing complications in general, even though specific healing complications may differ by their mechanism.

HIV shedding in the oral cavity: an assessment of HIV type, immunovirologic, demographic and oral factors.

OBJECTIVE: To quantify the prevalence and burden of HIV type 2 (HIV-2) and HIV-1 RNA in the oral cavity of antiretroviral therapy-naive HIV-infected Senegalese individuals and to identify correlates of oral HIV viral loads. DESIGN: A cross-sectional study of 163 HIV-1 and 27 HIV-2-infected antiretroviral therapy-naive Senegalese adults. METHODS: Participants received clinical and oral exams and provided blood and oral wash samples for viral load and plasma CD4 count ascertainment. Logistic and interval regression models were used to identify univariate and multivariable associations between presence and level of oral HIV RNA and various immunovirologic, local and demographic factors. RESULTS: Presence of detectable oral HIV RNA was less common in HIV-2-infected compared with HIV-1-infected study participants (33% vs 67%, OR 0.25, 95% CI 0.11 to 0.59). HIV type was no longer associated with oral shedding of HIV when plasma viral load was considered. Detection of oral HIV RNA was associated with increased plasma viral load in both HIV-1-infected and HIV-2-infected individuals (HIV-1, OR 1.89, 95% CI 1.24 to 2.61; HIV-2, OR 1.93, 95% CI 1.1 to 3.39). Oral HIV-1 detection was also associated with periodontal disease (OR 3.02, 95% CI 1.16 to 7.87). CONCLUSIONS: Oral shedding of HIV-2 RNA is less common than HIV-1 RNA, a likely consequence of lower overall viral burden. Both systemic and local factors may contribute to shedding of HIV in the oral cavity.

Relationship between epoetin alfa dose and mortality: findings from a marginal structural model.

BACKGROUND AND OBJECTIVES: Observational studies relating epoetin alfa (EPO) dose and mortality frequently use analytic methods that do not control time-dependent confounding by indication (CBI). The relationship between EPO dose and 1-year mortality, adjusting for the effects of time-dependent CBI, was examined using a marginal structural model. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: This retrospective cohort study included 27,791 hemodialysis patients between July 2000 and June 2002. Patients were grouped at successive 2-wk intervals into a zero-dose category or four nonzero-dose categories. Ordinal regression was used to calculate inverse probability of treatment weights of patients receiving their own dose level given their covariate and treatment history. Three treatment models with an increasing number of treatment predictors were evaluated to assess the effect of model specification. A small number of excessively large patient weights were truncated. Relative hazards for higher-dose groups compared with the lowest nonzero-dose group varied by treatment model specification and by level of weight truncation. RESULTS: Results differed appreciably between the simplest treatment model, which incorporated only hemoglobin and EPO dosing history with 2% weight truncation (hazard ratio: 1.51; 95% confidence interval: 1.09, 1.89 for highest-dose patients), and the most comprehensive treatment model with 1% weight truncation (hazard ratio: 0.98; 95% confidence interval: 0.76, 1.74). CONCLUSIONS: There is appreciable CBI at higher EPO doses, and EPO dose was not associated with increased mortality in marginal structural model analyses that more completely addressed this confounding.