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Purpose Identifying hospitalizations for serious infections among patients dispensed biologic therapies within healthcare databases is important for post-marketing surveillance of these drugs. We determined the positive predictive value (PPV) of an ICD-10-CM-based diagnostic coding algorithm to identify hospitalization for serious infection among patients dispensed biologic therapy within the FDA's Sentinel Distributed Database. Methods We identified health plan members who met the following algorithm criteria: (1) hospital ICD-10-CM discharge diagnosis of serious infection between July 1, 2016 and August 31, 2018; (2) either outpatient/emergency department infection diagnosis or outpatient antimicrobial treatment within 7 days prior to hospitalization; (3) inflammatory bowel disease, psoriasis, or rheumatological diagnosis within 1 year prior to hospitalization, and (4) were dispensed outpatient biologic therapy within 90 days prior to admission. Medical records were reviewed by infectious disease clinicians to adjudicate hospitalizations for serious infection. The PPV (95% confidence interval [CI]) for confirmed events was determined after further weighting by the prevalence of the type of serious infection in the database. Results Among 223 selected health plan members who met the algorithm, 209 (93.7% [95% CI, 90.1%-96.9%]) were confirmed to have a hospitalization for serious infection. After weighting by the prevalence of the type of serious infection, the PPV of the ICD-10-CM algorithm identifying a hospitalization for serious infection was 80.2% (95% CI, 75.3%-84.7%). Conclusions The ICD-10-CM-based algorithm for hospitalization for serious infection among patients dispensed biologic therapies within the Sentinel Distributed Database had 80% PPV for confirmed events and could be considered for use within pharmacoepidemiologic studies.

Background Evidence on the risk of febrile seizures (FS) after vaccination with inactivated influenza vaccine (IIV) and 13-valent pneumococcal conjugate vaccine (PCV13) is mixed. Among children 6–23 months, we examined the risk of FS following IIV and PCV13 during the 2013–14 and 2014–15 influenza seasons, for which vaccine virus strains were the same. Methods We used claims data from 4 large national insurers in the FDA-sponsored Sentinel Initiative, which was developed to monitor the safety of FDA-regulated medical products. With a self-controlled risk interval design, the risk of FS in 0–1 days following IIV and following PCV13 was compared with a comparison interval (14–20 days), adjusting for confounding by age, calendar time, and concomitant vaccination with the other vaccine. In exploratory analyses, we assessed whether the effect of IIV is modified by concomitant administration of PCV13. Results During the study period, 355,486 children received IIV and 581,868 received PCV13. We observed an incidence rate ratio (IRR) of 1.12 (95% CI 0.80, 1.56) for the risk of FS following IIV after adjustment for age, calendar time and concomitant PCV13. PCV13 was associated with an increased risk of FS (IRR adjusted for age, calendar time and concomitant IIV, 1.80, 95% CI 1.29, 2.52). The attributable risk for PCV13 ranged from 0.33 to 5.16 per 100,000 doses. The age and calendar-time adjusted IRR comparing exposed time to unexposed time was greater for concomitant IIV and PCV13 (IRR 2.80, 95% CI 1.63, 4.83), as compared with that for PCV13 without concomitant IIV (IRR 1.54, 95% CI 1.04, 2.28). However, the formal test assessing for interaction between IIV and PCV13 was not statistically significant. Conclusion We found an elevated risk of FS after PCV13 vaccine but not after IIV, when adjusting for concomitant administration of the other vaccine. We found some evidence to suggest that concomitant administration of IIV with PCV13 might interact to increase the risk beyond the independent effects of PCV13, but the study was not powered to assess this interaction. The risk of seizures associated with PCV13 is low compared with a child’s lifetime risk of FS. Findings should be interpreted in the context of the importance of preventing influenza and pneumococcal infections in young children. Disclosures L. Li, sanofi pasteur: The author is currently employed by Sanofi Genzyme, which shares the same parent company as sanofi pasteur, the manufacturer of the Flu vaccine. However, the work was done while this author was still employed by Harvard Pilgrim Health Care Institute., No financial benefit received

Background The Sentinel Initiative was established in 2008 to monitor the safety of FDA-regulated medical products. We evaluated the positive predictive value (PPV) of ICD-9 codes for post-vaccination febrile seizures to identify optimal algorithms for use in post-market safety surveillance. Methods We identified ICD-9 diagnosis codes for fever and seizures in the emergency department or inpatient setting after vaccinations of interest from July 1, 2010 to June 30, 2011. Medical record review was conducted to verify febrile seizure events. Results Of 216 potential febrile seizures identified with one or more seizure codes (the broadest algorithm), 152 were chart-confirmed (i.e., documentation of fever within 24 h of seizure or clinician diagnosis of febrile seizure; PPV 70%, 95% CI 64, 76%). Two codes specific for febrile seizures produced the highest PPV (PPV 91%, 95% CI 85, 95%) and accounted for 140 confirmed febrile seizures. In the absence of febrile seizure codes, other seizure codes yielded much lower PPVs, regardless of the presence of fever codes. Conclusions Our results indicate that ICD-9 diagnosis codes in the inpatient and emergency department settings have high predictive value for identifying febrile seizures within the Sentinel Distributed Database. While the PPV of the algorithm based on any diagnosis code for seizure is moderate, the algorithm limited to febrile seizure codes has a high PPV (>90%) and captures the vast majority of confirmed cases identified by the broadest algorithm, suggesting that the narrower algorithm limited to febrile seizure codes may be preferred.

Purpose Lymphoma is a health outcome of interest for drug safety studies. Studies using administrative claims data require the accurate identification of lymphoma cases. We developed and validated an International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM)-based algorithm to identify lymphoma in healthcare claims data. Methods We developed a three-component algorithm to identify patients aged ≥15 years who were newly diagnosed with Hodgkin (HL) or non-Hodgkin (NHL) lymphoma from January 2016 through July 2018 among members of four Data Partners within the FDA's Sentinel System. The algorithm identified potential cases as patients with ≥2 ICD-10-CM lymphoma diagnosis codes on different dates within 183 days; ≥1 procedure code for a diagnostic procedure (e.g. biopsy, flow cytometry) and ≥1 procedure code for a relevant imaging study within 90 days of the first lymphoma diagnosis code. Cases identified by the algorithm were adjudicated via chart review and a positive predictive value (PPV) was calculated. Results We identified 8,723 potential lymphoma cases via the algorithm and randomly sampled 213 for validation. We retrieved 138 charts (65%) and adjudicated 134 (63%). The overall PPV was 77% (95% Confidence Interval: 69-84%). Most cases also had subtype information available, with 88% of cases identified as NHL and 11% as HL. Conclusions Seventy-seven percent of lymphoma cases identified by an algorithm based on ICD-10-CM diagnosis and procedure codes and applied to claims data were true cases. This novel algorithm represents an efficient, cost-effective way to target an important health outcome of interest for large-scale drug safety and public health surveillance studies.

Valid algorithms for identification of cardiovascular (CV) deaths allow researchers to reliably assess the CV safety of medications, which is of importance to regulatory science, patient safety, and public health. The aim was to conduct a systematic review of algorithms to identify CV death in administrative health plan claims databases. We searched MEDLINE, EMBASE, and Cochrane Library for English-language studies published between January 1, 2012 and October 17, 2017. We examined references in systematic reviews to identify earlier studies. Selection included any observational study using electronic health care data to evaluate the sensitivity, specificity, positive predictive value (PPV), or negative predictive value (NPV) of algorithms for CV death (sudden cardiac death [SCD], myocardial infarction [MI]-related death, or stroke-related death) among adults aged ≥ 18 years in the United States. Data were extracted by two independent reviewers, with disagreements resolved through further discussion and consensus. The Quality Assessment of Diagnostic Accuracy Studies-2 instrument was used to assess the risk of bias. Five studies (n = 4 on SCD, n = 1 on MI- and stroke-related death) were included after a review of 2053 citations. All studies reported algorithm PPVs, with incomplete reporting on other accuracy parameters. One study was at low risk of bias, three studies were at moderate risk of bias, and one study was at unclear risk of bias. Two studies identified community-occurring SCD: one identified events using International Classification of Disease, Ninth Revision (ICD-9) codes on death certificates and other criteria from medical claims (PPV = 86.8%) and the other identified events resulting in hospital presentation using first-listed ICD-9 codes on emergency department or inpatient medical claims (PPV = 92.3%). Two studies used death certificates alone to identify SCD (PPV = 27% and 32%, respectively). One study used medical claims to identify CV death (PPV = 36.4%), coronary heart disease mortality (PPV = 28.3%), and stroke mortality (PPV = 34.5%). Two existing algorithms based on medical claims diagnoses with or without death certificates can accurately identify SCD to support pharmacoepidemiologic studies. Developing valid algorithms identifying MI- and stroke-related death should be a research priority. PROSPERO 2017 CRD42017078745.

Purpose Our purpose was to quantify missing baseline laboratory results, assess predictors of missingness, and examine performance of missing data methods. Methods Using the Mini-Sentinel Distributed Database from three sites, we selected three exposure–outcome scenarios with laboratory results as baseline confounders. We compared hazard ratios (HRs) or risk differences (RDs) and 95% confidence intervals (CIs) from models that omitted laboratory results, included only available results (complete cases), and included results after applying missing data methods (multiple imputation [MI] regression, MI predictive mean matching [PMM] indicator). Results Scenario 1 considered glucose among second-generation antipsychotic users and diabetes. Across sites, glucose was available for 27.7–58.9%. Results differed between complete case and missing data models (e.g., olanzapine: HR 0.92 [CI 0.73, 1.12] vs 1.02 [0.90, 1.16]). Across-site models employing different MI approaches provided similar HR and CI; site-specific models provided differing estimates. Scenario 2 evaluated creatinine among individuals starting high versus low dose lisinopril and hyperkalemia. Creatinine availability: 44.5–79.0%. Results differed between complete case and missing data models (e.g., HR 0.84 [CI 0.77, 0.92] vs. 0.88 [0.83, 0.94]). HR and CI were identical across MI methods. Scenario 3 examined international normalized ratio (INR) among warfarin users starting interacting versus noninteracting antimicrobials and bleeding. INR availability: 20.0–92.9%. Results differed between ignoring INR versus including INR using missing data methods (e.g., RD 0.05 [CI −0.03, 0.13] vs 0.09 [0.00, 0.18]). Indicator and PMM methods gave similar estimates. Conclusion Multi-site studies must consider site variability in missing data. Different missing data methods performed similarly. Copyright © 2016 John Wiley & Sons, Ltd.

Purpose To develop the infrastructure to conduct timely active surveillance for safety of influenza vaccines and other medical countermeasures in the Sentinel System (formerly the Mini-Sentinel Pilot), a Food and Drug Administration-sponsored national surveillance system that typically relies on data that are mature, settled, and updated quarterly. Methods Three Data Partners provided their earliest available (“fresh”) cumulative claims data on influenza vaccination and health outcomes 3–4 times on a staggered basis during the 2013–2014 influenza season, collectively producing 10 data updates. We monitored anaphylaxis in the entire population using a cohort design and seizures in children ≤4 years of age using both a self-controlled risk interval design (primary) and a cohort design (secondary). After each data update, we conducted sequential analysis for inactivated (IIV) and live (LAIV) influenza vaccines using the Maximized Sequential Probability Ratio Test, adjusting for data-lag. Results Most of the 10 sequential analyses were conducted within 6 weeks of the last care-date in the cumulative dataset. A total of 6 682 336 doses of IIV and 782 125 doses of LAIV were captured. The primary analyses did not identify any statistical signals following IIV or LAIV. In secondary analysis, the risk of seizures was higher following concomitant IIV and PCV13 than historically after IIV in 6- to 23-month-olds (relative risk = 2.7), which requires further investigation. Conclusions The Sentinel System can implement a sequential analysis system that uses fresh data for medical product safety surveillance. Active surveillance using sequential analysis of fresh data holds promise for detecting clinically significant health risks early. Limitations of employing fresh data for surveillance include cost and the need for careful scrutiny of signals. © 2015 The Authors. Pharmacoepidemiology and Drug Safety Published by John Wiley & Sons Ltd.

The effect of the type of surgical procedure on postoperative nausea and vomiting (PONV) rate has been debated in the literature. Our goal in this retrospective database study was to investigate the effect the type of surgical procedure (categorized and compared anatomically) has on antiemetic therapy within 2 h of admission to the postanesthesia care unit (PACU).We retrospectively analyzed data for oncology surgeries (n = 18,109), from our automated anesthesia information system database. We classified the types of surgical procedures anatomically into seven categories, with the integumentary musculoskeletal and the superficial surgeries chosen as the referent group. Our analysis included nine other risk factors for each patient, such as gender, smoking status, history of PONV or motion sickness, duration of anesthesia, number of prophylactic antiemetics administered, intraoperative opioids, ketorolac, epidural use, and postoperative opioids. Multivariate logistic regression was used to assess the effect of the type of surgery on antiemetic administration within the first 2 h of PACU admission, while adjusting for the other risk factors.Compared with integumentary musculoskeletal and superficial surgeries, patients undergoing neurological (P0.0001), head or neck (P0.0001), and abdominal (P0.0001) surgeries were administered PACU antiemetic significantly more often, whereas patients undergoing thoracic surgeries were administered PACU antiemetic significantly less often (P = 0.02). Breast or axilla (P = 0.74) and endoscopic (P = 0.28) procedures did not differ from the referent category. Female, nonsmoker, history of PONV or motion sickness, anesthesia duration, and intraoperative and postoperative opioid administration were significantly associated with antiemetic administration during early PACU admission.Using our automated anesthesia information system database, we found that the type of surgery, when categorized anatomically, was associated with an increased frequency of early PACU antiemetic administration in our population.

OBJECTIVES: In the Post-Licensure Rapid Immunization Safety Monitoring Program, we examined risk of febrile seizures (FS) after trivalent inactivated influenza vaccine (TIV) and 13-valent pneumococcal conjugate vaccine (PCV13) during the 2010–2011 influenza season, adjusted for concomitant diphtheria tetanus acellular pertussis-containing vaccines (DTaP). Assuming children would receive both vaccines, we examined whether same-day TIV and PCV13 vaccination was associated with greater FS risk when compared with separate-day vaccination. METHODS: We used a self-controlled risk interval design, comparing the FS rate in a risk interval (0–1 days) versus control interval (14–20 days). Vaccinations were identified in claims and immunization registry data. FS were confirmed with medical records. RESULTS: No statistically significant TIV-FS associations were found in unadjusted or adjusted models (incidence rate ratio [IRR] adjusted for age, seasonality, and concomitant PCV13 and DTaP: 1.36, 95% confidence interval [CI] 0.78 to 2.39). Adjusted for age and seasonality, PCV13 was significantly associated with FS (IRR 1.74, 95% CI 1.06 to 2.86), but not when further adjusting for concomitant TIV and DTaP (IRR 1.61, 95% CI 0.91 to 2.82). Same-day TIV and PCV13 vaccination was not associated with excess risk of FS when compared with separate-day vaccination (1.08 fewer FS per 100 000 with same day administration, 95% CI −5.68 to 6.09). CONCLUSIONS: No statistically significant increased risk of FS was found for 2010–2011 TIV or PCV13, when adjusting for concomitant vaccines. Same-day TIV and PCV13 vaccination was not associated with more FS compared with separate-day vaccination.

Purpose: The purpose of this research was to investigate the relationship between glutathione S-transferase (GST) polymorphisms and survival, and chemotherapy-related toxicity in 278 glioma patients. Experimental Design: We determined genetic variants for GSTM1, GSTT1, and GSTP1 enzymes by PCR and restriction fragment length polymorphisms. We conducted Kaplan-Meier and Cox-proportional hazard analyses to examine whether the GST polymorphisms are related to overall survival, and logistic regression analysis to explore whether the GST polymorphisms are associated with toxicity. Results: For patients with anaplastic astrocytoma, anaplastic oligodendroglioma, anaplastic oligoastrocytoma, and anaplastic ependymoma (n = 78), patients with GSTP1*A/*A-M1 null genotype survived longer than did the rest of the group (median survival “not achieved,” and 41 months, respectively; P = 0.06). Among patients treated with nitrosoureas (n = 108), those with GSTP1*A/*A and GSTM1 null genotype were 5.7 times (95% confidence interval, 0.9–37.4) more likely to experience an adverse event secondary to chemotherapy, compared with the others. Conclusions: In patients with anaplastic astrocytoma, anaplastic oligodendroglioma, and anaplastic oligoastrocytoma, combination of germ-line GSTP1*A/*A and GSTM1 null genotype confers a survival advantage. Patients with this genotype also have an increased risk of adverse events secondary to chemotherapy that primarily comprised nitrosourea alkylating agents.

International postlicensure studies have identified an increased risk of intussusception after vaccination with the second-generation rotavirus vaccines RotaTeq (RV5, a pentavalent vaccine) and Rotarix (RV1, a monovalent vaccine). We studied this association among infants in the United States.The study included data from infants 5.0 to 36.9 weeks of age who were enrolled in three U.S. health plans that participate in the Mini-Sentinel program sponsored by the Food and Drug Administration. Potential cases of intussusception and vaccine exposures from 2004 through mid-2011 were identified through procedural and diagnostic codes. Medical records were reviewed to confirm the occurrence of intussusception and the status with respect to rotavirus vaccination. The primary analysis used a self-controlled risk-interval design that included only vaccinated children. The secondary analysis used a cohort design that included exposed and unexposed person-time.The analyses included 507,874 first doses and 1,277,556 total doses of RV5 and 53,638 first doses and 103,098 total doses of RV1. The statistical power for the analysis of RV1 was lower than that for the analysis of RV5. The number of excess cases of intussusception per 100,000 recipients of the first dose of RV5 was significantly elevated, both in the primary analysis (attributable risk, 1.1 [95% confidence interval, 0.3 to 2.7] for the 7-day risk window and 1.5 [95% CI, 0.2 to 3.2] for the 21-day risk window) and in the secondary analysis (attributable risk, 1.2 [95% CI, 0.2 to 3.2] for the 21-day risk window). No significant increase in risk was seen after dose 2 or 3. The results with respect to the primary analysis of RV1 were not significant, but the secondary analysis showed a significant risk after dose 2.RV5 was associated with approximately 1.5 (95% CI, 0.2 to 3.2) excess cases of intussusception per 100,000 recipients of the first dose. The secondary analysis of RV1 suggested a potential risk, although the study of RV1 was underpowered. These risks must be considered in light of the demonstrated benefits of rotavirus vaccination. (Funded by the Food and Drug Administration.).

We describe a patient with metastases from neuroendocrine carcinoma masquerading as Graves ophthalmopathy. This rare tumour possibly has a propensity for orbital spread, and we postulate a mechanism evoking the 'seed and soil' hypothesis.

We aim to develop and validate the positive predictive value (PPV) of an algorithm to identify anaphylaxis using health plan administrative and claims data. Previously published PPVs for anaphylaxis using International Classification of Diseases, ninth revision, Clinical Modification (ICD-9-CM) codes range from 52% to 57%.We conducted a retrospective study using administrative and claims data from eight health plans. Using diagnosis and procedure codes, we developed an algorithm to identify potential cases of anaphylaxis from the Mini-Sentinel Distributed Database between January 2009 and December 2010. A random sample of medical charts (n = 150) was identified for chart abstraction. Two physician adjudicators reviewed each potential case. Using physician adjudicator judgments on whether the case met diagnostic criteria for anaphylaxis, we calculated a PPV for the algorithm.Of the 122 patients for whom complete charts were received, 77 were judged by physician adjudicators to have anaphylaxis. The PPV for the algorithm was 63.1% (95%CI: 53.9-71.7%), using the clinical criteria by Sampson as the gold standard. The PPV was highest for inpatient encounters with ICD-9-CM codes of 995.0 or 999.4. By combining only the top performing ICD-9-CM codes, we identified an algorithm with a PPV of 75.0%, but only 66% of cases of anaphylaxis were identified using this modified algorithm.The PPV for the ICD-9-CM-based algorithm for anaphylaxis was slightly higher than PPV estimates reported in prior studies, but remained low. We were able to identify an algorithm that optimized the PPV but demonstrated lower sensitivity for anaphylactic events.

A 66-year-old woman was hospitalized with a 2-month history of vaginal bleeding. Computed tomography and magnetic resonance imaging on admission showed a uterine tumor. The serum alpha-fetoprotein (AFP) level was 16,170 ng/ml (normal < 20). A total hysterectomy with bilateral salpingo-oophorectomy and regional lymphadenectomy were performed. A grayish-white tumor with focal necrotic areas was located in the posterior wall of the corpus uteri with smaller nodules in the lateral wall of the cervix. The tumor had two histologic patterns: one was a well-differentiated endometrioid adenocarcinoma and the other consisted of nests of cells resembling hepatocytes. In the hepatoid areas, giant cells and mitotic figures were frequent. Tumor cells in both the hepatoid areas and the glandular areas were immunoreactive for AFP. The tumor was diagnosed as a hepatoid adenocarcinoma of the uterus, the first described in this site, although 23 cases of hepatoid adenocarcinoma arising in the stomach, lung, kidney, ovary, duodenum, and urinary bladder have been reported.

The validity of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes to identify diagnoses of severe acute liver injury (SALI) is not well known. We examined the positive predictive values (PPVs) of hospital ICD-9-CM diagnoses in identifying SALI among health plan members in the Mini-Sentinel Distributed Database (MSDD) for patients without liver/biliary disease and for those with chronic liver disease (CLD).We selected random samples of members (149 without liver/biliary disease; 75 with CLD) with a principal hospital diagnosis suggestive of SALI (ICD-9-CM 570, 572.2, 572.4, 572.8, 573.3, 573.8, or V42.7) in the MSDD (2009-2010). Medical records were reviewed by hepatologists to confirm SALI events. PPVs of codes and code combinations for confirmed SALI were determined by CLD status.Among 105 members with available records and no liver/biliary disease, SALI was confirmed in 26 (PPV, 24.7%; 95%CI, 16.9-34.1%). Combined hospital diagnoses of acute hepatic necrosis (570) and liver disease sequelae (572.8) had high PPV (100%; 95%CI, 59.0-100%) and identified 7/26 (26.9%) events. Among 46 CLD members with available records, SALI was confirmed in 19 (PPV, 41.3%; 95%CI, 27.0-56.8%). Acute hepatic necrosis (570) or hepatorenal syndrome (572.4) plus any other SALI code had a PPV of 83.3% (95%CI, 51.6-97.9%) and identified 10/19 (52.6%) events.Most individual hospital ICD-9-CM diagnoses had low PPV for confirmed SALI events. Select code combinations had high PPV but did not capture all events.

Transparency in research methods and results is now widely seen as an imperative if the healthcare and research enterprise is to be truly successful. A patient-centred focus in the conduct of clinical care includes its safety, effectiveness, efficiency, equity, and timeliness. Innovative ways are being developed to understand, disseminate, and rapidly apply the best evidence to care delivery. In this article, we demonstrate the use of simple and appropriate statistics in research reports that should help healthcare providers apply knowledge to practice by making it easier for them to understand clinical medicine.

INTRODUCTION : Erythropoietin-stimulating agent (ESA) use is associated with serious adverse events in patients with hemoglobin levels of 12 g/dL or higher at the time of administration. Our aim was to determine whether inappropriate ESA use has changed over time since the implementation of new drug warning alerts and local quality improvement initiatives. MATERIALS AND METHODS : We performed a retrospective review of ESA administration practices at Memorial Hermann Healthcare System (Houston, Tex). Our primary outcome measure was the proportion of inpatient encounters (one entire inpatient hospital stay) with 1 or more inappropriate uses of ESA (defined as ESA administration for a patient with hemoglobin ≥12 g/dL). We analyzed the potential influence of local and national interventions on ESA utilization patterns. RESULTS : Between May 1, 2006, and May 31, 2009, 15,642 inpatients were treated with ESAs in our system. We classified inpatients as before intervention (n = 6350) and after intervention (n = 9292) based on the date of implementation of a synchronous alert in the electronic medical record. We found a significant decrease in inappropriate ESA administration before to after intervention (9.03%-6.21%; P < 0.001), which can be translated into a 31.25% (05% CI, 21.93%-40.75%) relative risk reduction. Reduced odds ratios for inappropriate ESA use changed little after controlling for relevant demographic variables and clinical characteristics. CONCLUSIONS : Following several quality improvement interventions to improve patient safety related to ESA use, we found a significant reduction in inappropriate ESA administration to inpatients in a large health care system.

Background The Breast Cancer Risk Assessment Tool of the National Cancer Institute (NCI) is widely used for counseling and determining eligibility for breast cancer prevention trials, although its validity for projecting risk in African American women is uncertain. We developed a model for projecting absolute risk of invasive breast cancer in African American women and compared its projections with those from the Breast Cancer Risk Assessment Tool. Methods Data from 1607 African American women with invasive breast cancer and 1647 African American control subjects in the Women’s Contraceptive and Reproductive Experiences (CARE) Study were used to compute relative and attributable risks that were based on age at menarche, number of affected mother or sisters, and number of previous benign biopsy examinations. Absolute risks were obtained by combining this information with data on invasive breast cancer incidence in African American women from the NCI’s Surveillance, Epidemiology and End Results Program and with national mortality data. Eligibility screening data from the Study of Tamoxifen and Raloxifene (STAR) trial were used to determine how the new model would affect eligibility, and independent data from the Women’s Health Initiative (WHI) were used to assess how well numbers of invasive breast cancers predicted by the new model agreed with observed cancers. Results Tables and graphs for estimating relative risks and projecting absolute invasive breast cancer risk with confidence intervals were developed for African American women. Relative risks for family history and number of biopsies and attributable risks estimated from the CARE population were lower than those from the Breast Cancer Risk Assessment Tool, as was the discriminatory accuracy (i.e., concordance). Using eligibility screening data from the STAR trial, we estimated that 30.3% of African American women would have had 5-year invasive breast cancer risks of at least 1.66% by use of the CARE model, compared with only 14.5% by use of the Breast Cancer Risk Assessment Tool. The numbers of cancers predicted by the CARE model agreed well with observed numbers of cancers (i.e., it was well calibrated) in data from the WHI, except that it underestimated risk in African American women with breast biopsy examinations. Conclusions The CARE model usually gave higher risk estimates for African American women than the Breast Cancer Risk Assessment Tool and is recommended for counseling African American women regarding their risk of breast cancer.

A focus on children and young adolescents in the primary prevention of health risks and disorders such as cancer, hypertension and other cardiovascular diseases, HIV/AIDS, and obesity has been suggested in many reports published throughout the world. Such a focus is important in India as it has a huge adolescents and children population along with the existing economic, social, and health inequalities among the general population. We propose a systematic elucidation of the rationale for such a focus in primary prevention research. We have reviewed studies describing risk factors, the association between risk factors and disease outcomes in affected patients, exposed populations, adolescent samples, as well as reports from studies conducted in India, and the quantitative and qualitative statistical aspects of research. The literature indicates that a lengthy time interval occurs between exposure to high risk factors and the development of disease, and that many such high risk exposures begin in young adolescence. These findings underline the value of targeting children and adolescents for primary prevention efforts in health care and health education for the attainment of overall healthy population in any country including a country like India.

The purpose is to investigate whether aggressive basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) differ from nonaggressive BCC and SCC with respect to the p53 mutation spectrum and whether specific mutations can serve as prognostic indicators of tumor aggressiveness.We analyzed 342 tissues from patients with aggressive and nonaggressive BCCs and SCCs for p53 mutations by single-strand conformation polymorphism and nucleotide sequencing.p53 mutations were detected in 33 of 50 aggressive BCCs (66%), 37 of 98 nonaggressive BCCs (38%), 28 of 80 aggressive SCCs (35%), 28 of 56 nonaggressive SCCs (50%), and 3 of 29 samples of sun-exposed skin (10%). About 71% of the p53 mutations detected in aggressive and nonaggressive BCCs and SCCs were UV signature mutations. The frequency of CC to TT mutations in aggressive (36%) and nonaggressive SCCs (39%) was 2-fold higher than in aggressive (18%) and nonaggressive (14%) BCCs. In contrast, aggressive BCCs had a higher frequency (24%) of transversions than nonaggressive BCCs (8%) and aggressive (14%) and nonaggressive (11%) SCCs did.Our results indicate that UV radiation is responsible for the induction of p53 mutations and perhaps for the initiation of both aggressive and nonaggressive BCCs and SCCs. Although some differences in p53 mutation frequency, types of mutation, and hot spots were seen between aggressive and nonaggressive BCCs and SCCs, these factors do not constitute as clear-cut diagnostic or prognostic indicators of tumor aggressiveness. Tumor aggressiveness may be attributable to other genetic changes or events that occur during tumor progression.