Cost-effectiveness of the McGill interactive pediatric oncogenetic guidelines in identifying Li-Fraumeni syndrome in female patients with osteosarcoma.

BACKGROUND: Li-Fraumeni syndrome (LFS) is a penetrant cancer predisposition syndrome (CPS) associated with the development of many tumor types in young people including osteosarcoma and breast cancer (BC). The McGill Interactive Pediatric OncoGenetic Guidelines (MIPOGG) decision-support tool provides a standardized approach to identify patients at risk of CPSs. METHODS: We conducted a cost-utility analysis, from the healthcare payer perspective, to compare MIPOGG-guided, physician-guided, and universal genetic testing strategies to detect LFS in female patients diagnosed at an age of less than 18 years with osteosarcoma. We developed a decision tree and discrete-event simulation model to simulate the clinical and cost outcomes of the three genetic referral strategies on a cohort of female children diagnosed with osteosarcoma, especially focused on BC as subsequent cancer. Outcomes included BC incidence, quality-adjusted life-years (QALYs), healthcare costs, and incremental cost-utility ratios (ICURs). We conducted probabilistic and scenario analyses to assess the uncertainty surrounding model parameters. RESULTS: Compared to the physician-guided testing, the MIPOGG-guided strategy was marginally more expensive by $105 (-$516; $743), but slightly more effective by 0.003 (-0.04; 0.045) QALYs. Compared to MIPOGG, the universal testing strategy was $1333 ($732; $1953) more costly and associated with 0.011 (-0.043; 0.064) additional QALYs. The ICUR for the MIPOGG strategy was $33,947/QALY when compared to the physician strategy; the ICUR for universal testing strategy was $118,631/QALY when compared to the MIPOGG strategy. DISCUSSION: This study provides evidence for clinical and policy decision-making on the cost-effectiveness of genetic referral strategies to identify LFS in the setting of osteosarcoma. MIPOGG-guided strategy was most likely to be cost-effective at a willingness-to-pay threshold value of $50,000/QALY.

Associations between specialized dementia care, COVID-19 and central nervous system medication use in assisted living: a population-based repeated cross-sectional study.

BACKGROUND: Assisted living (AL) is an increasingly common residential setting for persons with dementia; yet concerns exist about sub-optimal care of this population in AL given its lower levels of staffing and services. Our objectives were to (i) examine associations between AL setting (dementia care vs. other), COVID-19 pandemic waves, and prevalent antipsychotic, antidepressant, anti-dementia, benzodiazepine, and anticonvulsant drug use among residents with dementia/cognitive impairment, and (ii) explore associations between resident and home characteristics and prevalent medication use. METHODS: We conducted a population-based, repeated cross-sectional study using linked clinical and health administrative databases for all publicly funded AL homes in Alberta, Canada, examined between January 2018 - December 2021. The quarterly proportion of residents dispensed a study medication was examined for each setting and period (pandemic vs. comparable historical [2018/2019 combined]) focusing on four pandemic waves (March-May 2020, September 2020-February 2021, March-May 2021, September-December 2021). Log-binomial GEE models estimated prevalence ratios (PR) for period (pandemic vs. historical periods), setting (dementia care vs. other) and period-setting interactions, adjusting for resident (age, sex) and home (COVID-19 cases, health region, ownership) characteristics. RESULTS: On March 1, 2020, there were 2,779 dementia care and 3,013 other AL residents (mean age 83, 69% female) with dementia/cognitive impairment. Antipsychotic use increased during waves 2-4 in both settings, but this was more pronounced in dementia care than other AL during waves 3 and 4 (e.g., adjusted [adj]PR 1.20, 95% CI 1.14-1.27 vs. adjPR 1.09, 95% CI 1.02-1.17, interaction p = 0.023, wave 3). Both settings showed a statistically significant but modest increase in antidepressant use and decrease in benzodiazepine use. For dementia care AL residents only, there was a statistically significant increase in gabapentinoid use during several waves (e.g., adjPR 1.32, 95% CI 1.10-1.59, wave 3). Other than a modest decrease in prevalent anti-dementia drug use for both settings in wave 2, no other significant pandemic effects were observed. CONCLUSIONS: The persistence of the pandemic-associated increase in antipsychotic and antidepressant use in AL residents coupled with a greater increase in antipsychotic and gabapentinoid use for dementia care settings raises concerns about the attendant risks for residents with cognitive impairment.

Causal inference for recurrent events via aggregated marginal odds ratio.

Researchers often work with treatments and outcomes that vary over time. For example, psychologists are interested in the curative effect of cognitive behavior therapies on patients' recurrent depression symptoms. While there are various causal effect measures designed for one-time treatment, the causal effect measures for time-varying treatment and recurrent events are relatively under-developed. In this article, a new causal measure is proposed to quantify the causal effect of time-varying treatments on recurrent events. We suggest estimators with robust standard errors that are based on various weight models for both conventional causal measures and the proposed measure in different time settings. We outline the approaches and describe how using some stabilized inverse probability weight models are more advantageous than others. We demonstrate that the proposed causal estimand can be consistently estimated for study periods of moderate length, and the estimation results are compared under different treatment settings with various weight models. We also find that the proposed method is suitable for both absorbing and nonabsorbing treatments. The methods are applied to the 1997 National Longitudinal Study of Youth as an illustrative example.

Multiply robust estimation of causal quantile treatment effects.

In causal inference, often the interest lies in the estimation of the average causal effect. Other quantities such as the quantile treatment effect may be of interest as well. In this article, we propose a multiply robust method for estimating the marginal quantiles of potential outcomes by achieving mean balance in (a) the propensity score, and (b) the conditional distributions of potential outcomes. An empirical likelihood or entropy measure approach can be utilized for estimation instead of inverse probability weighting, which is known to be sensitive to the misspecification of the propensity score model. Simulation studies are conducted across different scenarios of correctness in both the propensity score models and the outcome models. Both simulation results and theoretical development indicate that our proposed estimator is consistent if any of the models are correctly specified. In the data analysis, we investigate the quantile treatment effect of mothers' smoking status on infants' birthweight.

Nonparametric analysis of dependently interval-censored failure time data.

Failure time studies based on observational cohorts often have to deal with irregular intermittent observation of individuals, which produces interval-censored failure times. When the observation times depend on factors related to a person's failure time, the failure times may be dependently interval censored. Inverse-intensity-of-visit weighting methods have been developed for irregularly observed longitudinal or repeated measures data and recently extended to parametric failure time analysis. This article develops nonparametric estimation of failure time distributions using weighted generalized estimating equations and monotone smoothing techniques. Simulations are conducted for examination of the finite sample performance of proposed estimators. This research is motivated in part by the Toronto Psoriatic Arthritis Cohort Study, and the proposed methodology is applied to this study.

Estimation of parametric failure time distributions based on interval-censored data with irregular dependent follow-up.

Event history studies based on disease clinic data often face several complications. Specifically, patients may visit the clinic irregularly, and the intermittent observation times could depend on disease-related variables; this can cause a failure time outcome to be dependently interval-censored. We propose a weighted estimating function approach so that dependently interval-censored failure times can be analysed consistently. A so-called inverse-intensity-of-visit weight is employed to adjust for the informative inspection times. Left truncation of failure times can also be easily handled. Additionally, in observational studies, treatment assignments are typically non-randomized and may depend on disease-related variables. An inverse-probability-of-treatment weight is applied to estimating functions to further adjust for measured confounders. Simulation studies are conducted to examine the finite sample performances of the proposed estimators. Finally, the Toronto Psoriatic Arthritis Cohort Study is used for illustration. Copyright © 2017 John Wiley & Sons, Ltd.

Development of a decision tree to classify the most accurate tissue-specific tissue to plasma partition coefficient algorithm for a given compound.

Physiologically based pharmacokinetic (PBPK) modeling is a tool used in drug discovery and human health risk assessment. PBPK models are mathematical representations of the anatomy, physiology and biochemistry of an organism and are used to predict a drug's pharmacokinetics in various situations. Tissue to plasma partition coefficients (Kp), key PBPK model parameters, define the steady-state concentration differential between tissue and plasma and are used to predict the volume of distribution. The experimental determination of these parameters once limited the development of PBPK models; however, in silico prediction methods were introduced to overcome this issue. The developed algorithms vary in input parameters and prediction accuracy, and none are considered standard, warranting further research. In this study, a novel decision-tree-based Kp prediction method was developed using six previously published algorithms. The aim of the developed classifier was to identify the most accurate tissue-specific Kp prediction algorithm for a new drug. A dataset consisting of 122 drugs was used to train the classifier and identify the most accurate Kp prediction algorithm for a certain physicochemical space. Three versions of tissue-specific classifiers were developed and were dependent on the necessary inputs. The use of the classifier resulted in a better prediction accuracy than that of any single Kp prediction algorithm for all tissues, the current mode of use in PBPK model building. Because built-in estimation equations for those input parameters are not necessarily available, this Kp prediction tool will provide Kp prediction when only limited input parameters are available. The presented innovative method will improve tissue distribution prediction accuracy, thus enhancing the confidence in PBPK modeling outputs.

Psychotropic, Anticonvulsant, and Opioid Use in Assisted Living Residents Before and During the COVID-19 Pandemic.

OBJECTIVES: To examine the associations between COVID-19 pandemic waves (1-4) and prevalent antipsychotic, antidepressant, benzodiazepine, anticonvulsant, and opioid use among assisted living (AL) residents, by setting (dementia care vs other). DESIGN: Population-based, repeated cross-sectional study. SETTING AND PARTICIPANTS: Linked clinical and health administrative databases for residents of all publicly subsidized AL homes (N = 256) in Alberta, Canada, examined from January 2018 to December 2021. Setting-specific quarterly cohorts of residents were derived for pandemic (starting March 1, 2020) and comparable historical (2018/2019 combined) periods. METHODS: The quarterly proportion of residents dispensed an antipsychotic, antidepressant, benzodiazepine, anticonvulsant, or opioid was examined for each setting and period. Log-binomial generalized estimating equations models estimated prevalence ratios (PR) for period (pandemic vs historical quarterly periods), setting (dementia care vs other AL), and period-setting interactions. RESULTS: On March 1, 2020, there were 2874 dementia care and 6611 other AL residents (mean age 82.4 vs 79.9 years, 68.2% vs 66.1% female, 93.5% vs 42.6% with dementia, respectively). Antipsychotic use increased during waves 2 to 4 for residents of both settings, but this increase was significantly greater for dementia care than other AL residents during waves 3 and 4 (eg, wave 3, PR 1.21, 95% CI 1.14-1.27 vs PR 1.12, 95% CI 1.07-1.17, interaction term P = .029). In both settings, there was a significant but modest increase in antidepressant use and a significant decrease in benzodiazepine use during several pandemic waves. For other AL residents only, there was a small statistically significant increase in anticonvulsant use during waves 2 to 4. No significant pandemic effect was observed for prevalent opioid use in either setting. CONCLUSIONS AND IMPLICATIONS: The persistence of the pandemic-associated increase in antipsychotic, antidepressant, and anticonvulsant use in AL residents, and greater increase in antipsychotic use for dementia care settings, raises concerns about the attendant risks for residents, especially those with dementia.

Inverse probability weighted estimating equations for randomized trials in transfusion medicine.

Thrombocytopenia is a condition characterized by extremely low platelet counts, which puts patients at elevated risk of morbidity and mortality because of bleeding. Trials in transfusion medicine are routinely designed to assess the effect of experimental platelet products on patients' platelet counts. In such trials, patients may receive multiple platelet transfusions over a predefined period of treatment, and a response is available from each such administration. The resulting data comprised multiple responses per patient, and although it is natural to want to use this data in testing for treatment effects, naive analyses of the multiple responses can yield biased estimates of the probability of response and associated treatment effects. These biases arise because only subsets of the patients randomized contribute response data on the second and subsequent administrations of therapy and the balance between treatment groups with respect to potential confounding factors is lost. We discuss the design and analysis issues involved in this setting and make recommendations for the design of future platelet transfusion trials.

Greater Opioid Use Among Nursing Home Residents in Ontario, Canada During the First 2 Waves of the COVID-19 Pandemic.

OBJECTIVES: To examine the association between the COVID-19 pandemic and opioid use among nursing home residents followed up to March 2021, and possible variation by dementia and frailty status. DESIGN: Population-based cohort study with an interrupted time series analysis. SETTING AND PARTICIPANTS: Linked health administrative databases for residents of all nursing homes (n = 630) in Ontario, Canada were examined. Residents were divided into consecutive weekly cohorts (first observation week was March 5 to 11, 2017 and last was March 21 to March 27, 2021). METHODS: The weekly proportion of residents dispensed an opioid was examined overall and by strata defined by the presence of dementia and frailty. Autoregressive Integrated Moving Average models with step and ramp intervention functions tested for immediate level and slope changes in weekly opioid use after the onset of the pandemic (March 1, 2020) and were fit on prepandemic data for projected trends. RESULTS: The average weekly cohort ranged from 76,834 residents (prepandemic) to 69,359 (pandemic period), with a consistent distribution by sex (69% female) and age (54% age 85 + years). There was a statistically significant increased slope change in the weekly proportion of residents dispensed opioids (parameter estimate (ß) = 0.035; standard error (SE) = 0.005, P < .001). Although significant for all 4 strata, the increased slope change was more pronounced among nonfrail residents (ß = 0.038; SE = 0.008, P < .001) and those without dementia (ß = 0.044; SE = 0.008, P < .001). The absolute difference in observed vs predicted opioid use in the last week of the pandemic period ranged from 1.25% (frail residents) to 2.28% (residents without dementia). CONCLUSIONS AND IMPLICATIONS: Among Ontario nursing home residents, there was a statistically significant increase in opioid dispensations following the onset of the pandemic that persisted up to 1 year later. Investigations of the reasons for increased use, potential for long-term use and associated health consequences for residents are warranted.

Correlates of Opioid Use Among Ontario Long-Term Care Residents and Variation by Pain Frequency and Intensity: A Cross-sectional Analysis.

BACKGROUND: Chronic non-cancer pain is common among older residents of long-term care (LTC) homes and often poorly recognized and treated. With heightened concerns regarding opioid prescribing in recent years, it is important to examine the current prevalence of opioid use and its association with resident characteristics to help identify those potentially at risk of medication harms as well as suboptimal pain management. OBJECTIVES: The aims were to estimate the prevalence and correlates of opioid use among non-palliative LTC residents and explore variation in opioid prevalence and correlates across strata defined by pain frequency and intensity. METHODS: We conducted a population-based cross-sectional study of all older (aged > 65 years) LTC residents (excluding those with cancer or receiving palliative care) in Ontario, Canada during 2018-2019. Health administrative databases were linked with standardized clinical assessment data to ascertain residents' health and pain characteristics and their opioid and other medication use. Modified Poisson regression models estimated unadjusted and adjusted associations between residents' characteristics and opioid use, overall and across strata capturing pain frequency and intensity. RESULTS: Among 75,020 eligible residents (mean age 85.1 years; 70% female), the prevalence of opioid use was 18.5% and pain was 29.4%. Opioid use ranged from 12.2% for residents with no current pain to 55.7% for those with severe pain. In adjusted models, residents newly admitted to LTC (adjusted risk ratio [aRR] = 0.60, 95% confidence interval [CI] 0.57-0.62) and with moderate to severe cognitive impairment (aRR = 0.69, 95% CI 0.66-0.72) or dementia (aRR = 0.76, 95% CI 0.74-0.79) were significantly less likely to receive an opioid, whereas residents with select conditions (e.g., arthritis, aRR = 1.37, 95% CI 1.32-1.41) and concurrently using gabapentinoids (aRR = 1.80, 95% CI 1.74-1.86), benzodiazepines (aRR = 1.33, 95% CI 1.28-1.38), or antidepressants (aRR = 1.31, 95% CI 1.27-1.35) were significantly more likely to receive an opioid. The associations observed for residents newly admitted, with dementia, and concurrently using gabapentinoids, benzodiazepines, or antidepressants were largely consistent across all pain strata. CONCLUSIONS: Our findings describe resident sub-groups at potentially higher risk of adverse health outcomes in relation to both opioid use and non-use. LTC clinical and policy changes informed by research are required to ensure the appropriate recognition and management of non-cancer pain in this setting.

Comparison of Medication Prescribing Before and After the COVID-19 Pandemic Among Nursing Home Residents in Ontario, Canada.

Importance: COVID-19 has had devastating effects on the health and well-being of older adult residents and health care professionals in nursing homes. Uncertainty about the associated consequences of these adverse effects on the use of medications common to this care setting remains. Objective: To examine the association between the COVID-19 pandemic and prescription medication changes among nursing home residents. Design, Setting, and Participants: This population-based cohort study with an interrupted time-series analysis used linked health administrative data bases for residents of all nursing homes (N = 630) in Ontario, Canada. During the observation period, residents were divided into consecutive weekly cohorts. The first observation week was March 5 to 11, 2017; the last observation week was September 20 to 26, 2020. Exposures: Onset of the COVID-19 pandemic on March 1, 2020. Main Outcomes and Measures: Weekly proportion of residents dispensed antipsychotics, benzodiazepines, antidepressants, anticonvulsants, opioids, antibiotics, angiotensin receptor blockers (ARBs), and angiotensin-converting enzyme (ACE) inhibitors. Autoregressive integrated moving average models with step and ramp intervention functions tested for level and slope changes in weekly medication use after the onset of the pandemic and were fit on prepandemic data for projected trends. Results: Across study years, the annual cohort size ranged from 75 850 to 76 549 residents (mean [SD] age, 83.4 [10.8] years; mean proportion of women, 68.9%). A significant increased slope change in the weekly proportion of residents who were dispensed antipsychotics (parameter estimate [ß] = 0.051; standard error [SE] = 0.010; P < .001), benzodiazepines (ß = 0.026; SE = 0.003; P < .001), antidepressants (ß = 0.046; SE = 0.013; P < .001), trazodone hydrochloride (ß = 0.033; SE = 0.010; P < .001), anticonvulsants (ß = 0.014; SE = 0.006; P = .03), and opioids (ß = 0.038; SE = 0.007; P < .001) was observed. The absolute difference in observed vs estimated use in the last week of the pandemic period ranged from 0.48% (for anticonvulsants) to 1.52% (for antipsychotics). No significant level or slope changes were found for antibiotics, ARBs, or ACE inhibitors. Conclusions and Relevance: In this population-based cohort study, statistically significant increases in the use of antipsychotics, benzodiazepines, antidepressants, anticonvulsants, and opioids followed the onset of the COVID-19 pandemic, although absolute differences were small. There were no significant changes for antibiotics, ARBs, or ACE inhibitors. Studies are needed to monitor whether changes in pharmacotherapy persist, regress, or accelerate during the course of the pandemic and how these changes affect resident-level outcomes.

Cost-Utility of Early Breast Cancer Surveillance in Survivors of Thoracic Radiation-Treated Adolescent Hodgkin Lymphoma.

BACKGROUND: Adolescent women treated for Hodgkin lymphoma (HL) are at increased risk of breast cancer (BC). We evaluate the cost-utility of eight high-risk BC surveillance strategies for this population, including the Children's Oncology Group guideline of same-day annual mammography and magnetic resonance imaging (MRI) beginning at age 25 years. METHODS: A discrete event simulation model was used to simulate the life histories of a cohort of 500 000 25-year-old women treated for HL at age 15 years. We estimated BC incidence and mortality, life expectancy, quality-adjusted life-years (QALYs), health-care costs, and the relative cost-utility (incremental cost-utility ratio [ICUR]) under the eight assessed surveillance strategies. One-way sensitivity analysis enabled modeling of uncertainty evaluation. A publicly funded health-care payer perspective was adopted. RESULTS: Costs across the eight screening strategies ranged from $32 643 to $43 739, whereas QALYs ranged from 24.419 to 24.480. In an incremental cost-effectiveness analysis, annual mammography beginning at age 25 years was associated with an ICUR of $43 000/QALY gained, annual MRI beginning at age 25 years with a switch to annual mammography at age 50 years had an ICUR of $148 000/QALY, and annual MRI beginning at age 25 years had an ICUR of $227 222/QALY. Among all assessed surveillance strategies, the differences in life expectancy were small. CONCLUSIONS: Current high-risk BC surveillance guidelines do not reflect the most cost-effective strategy in survivors of adolescent HL. The results suggest that groups at high risk of BC may require high-risk surveillance guidelines that reflect their specific risk profile.

A model averaging approach for estimating propensity scores by optimizing balance.

Many approaches, including traditional parametric modeling and machine learning techniques, have been proposed to estimate propensity scores. This paper describes a new model averaging approach to propensity score estimation in which parametric and nonparametric estimates are combined to achieve covariate balance. Simulation studies are conducted across different scenarios varying in the degree of interactions and nonlinearities in the treatment model. The results show that, based on inverse probability weighting, the proposed propensity score estimator produces less bias and smaller standard errors than existing approaches. They also show that a model averaging approach with the objective of minimizing the average Kolmogorov-Smirnov statistic leads to the best performing IPW estimator. The proposed approach is also applied to a real data set in evaluating the causal effect of formula or mixed feeding versus exclusive breastfeeding on a child's body mass index Z-score at age 4. The data analysis shows that formula or mixed feeding is more likely to lead to obesity at age 4, compared to exclusive breastfeeding.

Anticonvulsants for behavioral and psychological symptoms in dementia: protocol for a systematic review.

BACKGROUND: Behavioral and psychological symptoms of dementia (BPSD) are present in a majority of patients with dementia contributing to increased morbidity, health care costs, and caregiver burden. While there are no United States Food and Drug Administration (FDA)-approved medications for these symptoms, off-label use of medications such as antipsychotics have been shown to have significant adverse effects including increased mortality. The goal of this review is to examine the efficacy and safety of anticonvulsants in the treatment of BPSD. METHODS: We will systematically search for randomized trials of anticonvulsants compared to placebo or other treatments such as antidepressants and antipsychotics from the following sources: The Cochrane Library, MEDLINE (OVID SP) in Process and Other Non-Indexed Citations (latest version), EMBASE, clinicalTrials.gov , and the WHO Clinical Trials Registry. The studies will be limited to those published in English but the study location can be worldwide. We will include studies pertaining to individuals with dementia and symptoms of BPSD. The primary outcomes will be behavioral change as measured by validated scales and secondary outcomes will include caregiver burden, quality of life, placement in long term care facility, serious adverse effects, and treatment discontinuation due to adverse effects. Two sets of reviewers will independently screen select and extract data. We will narratively describe the major findings and conclusions from individual studies. Patients who are prescribed antiepileptic drugs (AEDs) for other indications, including seizures, will be excluded. Outcomes of interest will include a change in a validated scale that measures BPSD, serious adverse events, and caregiver quality of life outcomes. If the data are found to be appropriate for a meta-analysis, we will use a random effects model to compute summary estimates of treatment effects. DISCUSSION: This is a protocol for a systematic review addressing the anticonvulsant group of medications as a whole, and as such, our results will inform current clinical practice in the use of anticonvulsants for BPSD. It will also help clinicians and policy makers compare the efficacy of anticonvulsants compared to antidepressants and antipsychotics as well as identify areas which will need further study. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42017079826.

Treatment of Wilms tumor relapsing after initial treatment with vincristine, actinomycin D, and doxorubicin. A report from the National Wilms Tumor Study Group.

OBJECTIVE: We evaluated the use of alternating cycles of cyclophosphamide/etoposide and carboplatin/etoposide in children entered on National Wilms Tumor Study (NWTS)-5 who were diagnosed between August 1, 1995 and May 31, 2002 and who relapsed after chemotherapy with vincristine, actinomycin D, and doxorubicin (VAD) and radiation therapy (DD-4A). PATIENTS AND METHODS: One hundred three patients who relapsed or had progressive disease after initial VAD chemotherapy and radiation therapy were registered on stratum C of the NWTS-5 Relapse protocol. Twelve patients were not evaluable: five due to insufficient data, six due to major protocol violations, and one for refusal of therapy. Among the 91 remaining patients, 14 with stage V Wilms tumor (WT), 1 with contralateral relapse, and 16 who did not achieve a complete response (CR) to the initial three-drug chemotherapy were not included in this analysis. Relapse treatment included alternating courses of the drug pairs cyclophosphamide/etoposide and carboplatin/etoposide, surgery, and radiation therapy. RESULTS: The outcomes of 60 patients were analyzed. The lung was the only site of relapse for 33 patients; other sites of relapse included the operative bed, the abdomen, and liver. Four-year event-free survival (EFS) and overall survival (OS) were 42.3 and 48.0% respectively for all patients and were 48.9 and 52.8% for those who relapsed in the lungs only. Thrombocytopenia was the most frequent toxicity. CONCLUSION: These results demonstrate that approximately one-half of children with unilateral WT who relapse after initial treatment with VAD and radiation therapy can be successfully retreated.

Mortality ascertainment of participants in the National Wilms Tumor Study using the National Death Index: comparison of active and passive follow-up results.

Long term studies of childhood cancer survivors are hampered by difficulties in tracking young adult participants. After performing a National Death Index (NDI) search we sought to identify which factors best predicted a match among known decedents from the National Wilms Tumor Study (NWTS) and to determine if record linkage could substitute for missing follow-up in a cohort of NWTS survivors. To our knowledge, this is the first study to compare passive mortality follow-up using the NDI to active follow-up of a childhood and young adult population. Records for 984 known decedents and 3,406 subjects whose January 1, 2002 vital status was unknown were sent to the NDI in June 2003. In April 2005 NWTS follow-up records were used to reassess January 1, 2002 vital status. Matches were established for 709 of 789 known decedents (sensitivity 89.9%) with a date of death between 1979 and 2001, the calendar period covered by the NDI at the time of the search. No matches were identified among 1,052 subjects known to be alive in 2002 (specificity 100%). Factors associated with decreased sensitivity were an unknown social security number (sensitivity 87.8%), Hispanic ethnicity (76.4%) and foreign birth (56.5%). For 2,351 subjects with 2002 vital status unknown who had 13,166 pre 2002 person-years of missing observation, only 18 deaths were ascertained by the NDI whereas 79.3 were expected based on NWTS mortality data. Mortality analyses based strictly on NDI search results and those based on NWTS follow-up augmented with NDI search results yielded inflated estimates of the 15 year survival rate when compared with estimates based on NWTS active follow-up. Match rates were comparable to those observed in adult populations. Since the same selection factors were likely associated with NDI failure to match and NWTS loss to follow-up, use of the NDI to fill in missing follow-up data appears unwarranted.

Impact of Early Breast Cancer Screening on Mortality Among Young Survivors of Childhood Hodgkin's Lymphoma.

BACKGROUND: Female survivors treated with thoracic radiation therapy (RT) for childhood cancer experience increased risks of breast cancer (BC). There are currently no data quantifying the potential mortality gains of early BC screening among such survivors. METHODS: A mathematical model of BC development was used to evaluate the marginal benefit of early-initiated screening of female survivors of adolescent Hodgkin's lymphoma (HL) starting at age 25 years on BC mortality compared with screening initiated at age 40 years. Sensitivity analyses were performed to evaluate the robustness of the estimates over a plausible range of conditions. RESULTS: For survivors treated at age 15 years, the absolute risk of BC mortality by age 75 years was predicted to decrease from 16.65% with no early screening to 16.28% (annual mammography), 15.40% (annual MRI), 15.38% (same-day annual mammography and MRI), and 15.37% (alternating mammography and MRI every six months). Approximately 80 patients would need to be invited to MRI-based screening to prevent one BC death. In sensitivity analyses, the number needed to invite to MRI-based screening to prevent one BC death ranged from 71 to 333. Combinations of MRI plus mammography were predicted to produce 99.52 false positives per 1000 screenings done between age 25 to 39 years. CONCLUSIONS: These findings are the first to indicate that early MRI-based screening should reduce BC mortality among women treated with RT for adolescent HL. The magnitude of this benefit is superior to that described for other accepted screening indications although MRI can produce a substantial rate of false-positive results.

Early and late mortality after diagnosis of wilms tumor.

PURPOSE: To assess rates and causes of mortality in patients with Wilms tumor (WT). METHODS: Through 2002, 6,185 patients enrolled onto the National Wilms Tumor Study between 1969 and 1995 were actively observed. Deaths were classified on the basis of medical records as the result of original disease, late effects (including second malignant neoplasms [SMNs], cardiac causes, pulmonary disease, and renal failure), or other causes. Standardized mortality ratios (SMRs) and Cox regression were used to assess the effects of sex, age, and calendar period of diagnosis on mortality. RESULTS: Within 5 years of WT diagnosis, 819 deaths occurred, and 159 deaths occurred among 4,972 known 5-year survivors. The SMR was 24.3 (95% CI, 22.6 to 26.0) for the first 5 years, was 12.6 (95% CI, 10.0 to 15.7) for the next 5 years, and remained greater than 3.0 thereafter. For deaths in the first 5 years, the mortality risk decreased by 5-year calendar period of diagnosis (rate ratio [RR] = 0.78 per period). No such trend occurred for later deaths. Among 5-year survivors, 62 deaths were attributed to late effects of treatment or disease, including 27 to SMNs. A trend of decreased risk with calendar period of diagnosis was observed for late-effects mortality (RR = 0.86; 95% CI, 0.67 to 1.10) and for SMN mortality (RR = 0.82; 95% CI, 0.55 to 1.21). CONCLUSION: Although the survival outlook for WT patients has improved greatly over time, survivors remain at elevated risk for death many years after their original diagnosis.