Relationships between migration and the fiscal sustainability of the pension system in China

There are a few existing studies on whether domestic migration improves China's pension system's fiscal sustainability in the context of rapid urbanization and industrialization. In this paper, we systematically investigate the impact of migration on the solvency of the worker's old-age insurance for urban employees by constructing actuarial and econometric models. We use panel data from 2002 to 2018, collected from 31 provinces in China. The results show that the association between migration and the solvency of pensions is an inverted-U shape along the urbanization process. Further regional comparison showed that the above-stated inverted-U curve is more pronounced in the central and western regions. We also established that the number of participants and the contribution base are the main contributors to these results. Our conclusions are important for future population policies and public pension systems in China.

[Rare diseases from a life insurance perspective]

A rare disease is defined as a disease that affects a maximum of 5 in 10,000 people. As of today there are roughly 7000 different rare diseases known. On account of this one can say that "rare diseases are rare, but people affected by them are common". For Germany this amounts to: 4 million people that are affected by a rare disease. Diagnosis, therapeutic options and prognosis have substantially improved for some of the rare diseases. Besides the general medical advances--especially in the area of genetics--this is also due to networking and sharing information by so-called Centres of Competence on a national and international scale. This results in a better medical care for the corresponding group of patients. Against this backdrop, the number of people applying for life assurance who are suffering from a complex or rare disease has risen steadily in the last years. Due to the scarce availability of data regarding long-term prognosis of many rare diseases, a biomathematical, medical and actuarial expertise on the part of the insurer is necessary in order to adequately assess the risk of mortality and morbidity. Furthermore there is quite a focus on the issue of rare diseases from not only politics but society as well. Therefore evidence based medical assessment by insurers is especially important in this group of applicants--thinking of legal compliance and reputational risk.

Actuarial considerations of medical malpractice evaluations in M&As

To best project an actuarial estimate for medical malpractice exposure for a merger and acquisition, a organization's leaders should consider the following factors, among others: How to support an unbiased actuarial estimation. Experience of the actuary. The full picture of the organization's malpractice coverage. The potential for future loss development. Frequency and severity trends.

Population forecasts for Bangladesh, using a Bayesian methodology

Population projection for many developing countries could be quite a challenging task for the demographers mostly due to lack of availability of enough reliable data. The objective of this paper is to present an overview of the existing methods for population forecasting and to propose an alternative based on the Bayesian statistics, combining the formality of inference. The analysis has been made using Markov Chain Monte Carlo (MCMC) technique for Bayesian methodology available with the software WinBUGS. Convergence diagnostic techniques available with the WinBUGS software have been applied to ensure the convergence of the chains necessary for the implementation of MCMC. The Bayesian approach allows for the use of observed data and expert judgements by means of appropriate priors, and a more realistic population forecasts, along with associated uncertainty, has been possible.

The efficiency of a group-specific mandated benefit revisited: the effect of infertility mandates

This paper examines the labor market effects of state health insurance mandates that increase the cost of employing a demographically identifiable group. State mandates requiring that health insurance plans cover infertility treatment raise the relative cost of insuring older women of child-bearing age. Empirically, wages in this group are unaffected, but their total labor input decreases. Workers do not value infertility mandates at cost, and so will not take wage cuts in exchange, leading employers to decrease their demand for this affected and identifiable group. Differences in the empirical effects of mandates found in the literature are explained by a model including variations in the elasticity of demand, moral hazard, ability to identify a group, and adverse selection.

Selection in insurance markets: theory and empirics in pictures

Government intervention in insurance markets is ubiquitous and the theoretical basis for such intervention, based on classic work from the 1970s, has been the problem of adverse selection. Over the last decade, empirical work on selection in insurance markets has gained considerable momentum. This research finds that adverse selection exists in some insurance markets but not in others. And it has uncovered examples of markets that exhibit "advantageous selection"—a phenomenon not considered by the original theory, and one that has different consequences for equilibrium insurance allocation and optimal public policy than the classical case of adverse selection. Advantageous selection arises when the individuals who are willing to pay the most for insurance are those who are the most risk averse (and so have the lowest expected cost). Indeed, it is natural to think that in many instances individuals who value insurance more may also take action to lower their expected costs: drive more carefully, invest in preventive health care, and so on. Researchers have taken steps toward estimating the welfare consequences of detected selection and of potential public policy interventions. In this essay, we present a graphical framework for analyzing both theoretical and empirical work on selection in insurance markets. This graphical approach provides both a useful and intuitive depiction of the basic theory of selection and its implications for welfare and public policy, as well as a lens through which one can understand the ideas and limitations of existing empirical work on this topic.

A time series modeling approach in risk appraisal of violent and sexual recidivism

For over half a century, various clinical and actuarial methods have been employed to assess the likelihood of violent recidivism. Yet there is a need for new methods that can improve the accuracy of recidivism predictions. This study proposes a new time series modeling approach that generates high levels of predictive accuracy over short and long periods of time. The proposed approach outperformed two widely used actuarial instruments (i.e., the Violence Risk Appraisal Guide and the Sex Offender Risk Appraisal Guide). Furthermore, analysis of temporal risk variations based on specific time series models can add valuable information into risk assessment and management of violent offenders.

ANTEROCOD: actuarial survival curves applied to medical coding support for chronic diseases

For the practitioner, choosing diagnosis codes is a non-intuitive operation. Mistakes are frequent, causing severe consequences on healthcare performance evaluation and funding. French physicians have to assign a code to all their activities and are frequently prone to these errors. Given that most of the time and particularly for chronic diseases indexed information is already available, we propose a tool named AnterOcod, in order to support the medical coding task. It suggests the list of most relevant plausible codes, predicted from the patient's earlier hospital stays, according to a set of previously utilized diagnosis codes. Our method applies the estimation of code reappearance rates, based on an equivalent approach to actuarial survival curves. Around 33% of the expected correct diagnosis codes were retrieved in this manner, after evaluating 998 discharge abstracts, significantly improving the coding task.

Actuarial assessment of violence risk in hospital-based partner assault clinics

Hospital-based partner assault clinics are a relatively recent addition to the community response to partner violence. In this study, 66% of 111 women attending hospital clinics for partner assault were physically injured and 43% reported death threats. Few concurrently used other services (shelters or police) and most relied on female friends and relatives for help. Many participants who currently lived with the perpetrator were contemplating leaving but only a third had made plans to do so. Participants faced an unusually high risk of future assault, according to both victim interview using the ODARA actuarial risk assessment and their own perceptions. Findings imply an important role for partner assault clinics and the feasibility of the victim service sector's using the same actuarial risk assessments as the criminal justice system.

[Decision analysis--a novel approach for calculating the cost-efficiency of medical tests]

Before issuing an insurance policy (e.g. life, disability, critical illness), insurers will usually carry out a medical risk assessment in order to prevent adverse selection. Often, the health questions in the application form will not be sufficient for this purpose since most applicants are not well-versed in medical science and terminology. If the insurer needs additional medical information such as a private medical attendant's report or current laboratory tests, however, costs will be incurred, which usually have to be paid by the insurer. What is the minimum sum insured which makes it worthwhile for the insurer to conduct certain screening tests, for example? Both the costs of medical screening and the associated savings are difficult to measure and involve a variety of different factors. Moreover, most parameters can only be estimated with limited accuracy. Therefore, we have developed a new calculation model using a decision-analysis approach. The new model makes it possible to analyse complex situations while taking into account the uncertainty of parameter estimation. Our findings show that in Germany, for instance, current sum thresholds for older applicants could in many cases be lowered and would still be cost-effective.

Risk and safety assessment in child welfare: instrument comparisons

The assessment of risk is a critical part of child welfare agency practice. This review of the research literature on different instruments for assessing risk and safety in child welfare focuses on instrument reliability, validity, outcomes, and use with children and families of color. The findings suggest that the current actuarial instruments have stronger predictive validity than consensus-based instruments. This review was limited by the variability in definitions and measures across studies, the relatively small number of studies examining risk assessment instruments, and the lack of studies on case decision points other than the initial investigation.

Unguided clinical and actuarial assessment of re-offending risk: a direct comparison with sex offenders in Denmark

Meta-analyses suggest that actuarial risk assessments outperform unguided clinical judgment for prediction of recidivism in criminal offenders. However, there is a lack of direct comparisons of the predictive accuracy of clinical judgment and actuarial risk scales for sexual offenders. We followed up 121 male sex offenders (> or =18 years) subjected to pre-trial forensic psychiatric assessment in Denmark in 1978-1992 (mean post-detainment time = 16.4 years) to compare the predictive validity of unstructured clinical judgment of recidivism risk with that of the well-established Static-99 (Hanson and Thornton, Law and Human Behavior 24:119-136, 2000) and an extension of the Static-99, the Static-2002 (Hanson and Thornton, Notes on the development of Static-2002 (Rep. No. 2003-01), Public Safety and Emergency Preparedness Canada, Ottawa, Canada, 2003). The predictive accuracy of unguided judgment did not exceed chance for any sexual, severe sexual or any violent (sexual or non-sexual) reconviction (AUCs of the ROC curve = 0.52, 95%CI = 0.41-0.63; 0.50, 95%CI = 0.34-0.67; and 0.57, 95%CI = 0.40-0.73, respectively). In contrast, all three outcomes were predicted significantly better than chance by the Static-99 (AUC = 0.62, 95%CI = 0.52-0.72; 0.72, 95%CI = 0.59-0.84; and 0.71, 95%CI = 0.56-0.86) and the Static-2002 (AUC = 0.67, 95%CI = 0.57-0.77; 0.69, 95%CI = 0.56-0.83; and 0.70, 95%CI = 0.55-0.86). Static-99 outperformed clinical judgment for sexual recidivision (chi(2) = 5.11, df = 1, p < .05). The Static-2002 was significantly more accurate for the prediction of any sexual recidivism as compared to unguided clinical judgment but its advantage fell just short of statistical significance for severe sexual recidivism (chi(2) = 3.56, df = 1, p = 0.06). When tested for recidivism within 2 years, none of the three prediction methods yielded results significantly better than chance for any outcome. This direct trial of the unguided clinical method argues against its continued use for risk assessment of sexual offenders.

Pivot tables for mortality analysis, or who needs life tables anyway?

Actuarial life-table analysis has long been used by life insurance medical directors for mortality abstraction from clinical studies. Ironically, today's life actuary instead uses pivot tables to analyze mortality. Pivot tables (a feature/function in MS Excel) collapse various dimensions of data that were previously arranged in an "experience study" format. Summary statistics such as actual deaths, actual and expected mortality (usually measured in dollars), and calculated results such as actual to expected ratios, are then displayed in a 2-dimensional grid. The same analytic process, excluding the dollar focus, can be used for clinical mortality studies. For raw survival data, especially large datasets, this combination of experience study data and pivot tables has clear advantages over life-table analysis in both accuracy and flexibility. Using the SEER breast cancer data, we compare the results of life-table analysis and pivot-table analysis.

Predictive medical information and underwriting

Medical underwriting involves the application of actuarial science by analyzing medical information to predict the future risk of a claim. The objective is that individuals with like risk are treated in a like manner so that the premium paid is proportional to the risk of future claim.

The factor structure of static actuarial items: its relation to prediction

Principal components analysis was conducted on items contained in actuarial instruments used with adult sex offenders, including: the Rapid Assessment of Sex Offender Risk for Recidivism (RASORR), the Static-99, the Violence Risk Appraisal Guide (VRAG), the Sex Offender Risk Appraisal Guide (SORAG), and the Minnesota Sex Offender Screening Tool-Revised (MnSOST-R). In a data set that included child molesters and rapists (N = 311), six interpretable components were identified: Antisocial Behavior, Child Sexual Abuse, Persistence, Detached Predatory Behavior, Young and Single, and Male Victim(s). The RRASOR was highly correlated with Persistence, and the VRAG and SORAG were highly correlated with Antisocial Behavior. Antisocial Behavior was a significant predictor of violent recidivism, while Persistence and Child Sexual Abuse were significant predictors of sexual recidivism.

Comparison of two risk assessment instruments for sexual offenders

The current research examines the predictive validity of the Static-99 and the SORAG in predicting sexual and violent recidivism among a sample of 258 treated high-risk sexual offenders. While the SORAG was found to have moderate predictive accuracy for both sexual and violent recidivism over a 5-year follow-up period, the Static-99 was found to only predict sexual recidivism. As well, the actual recidivism rates in the current sample were compared to the published risk percentages for each of the instruments. For both the Static-99 and the SORAG the current sample re-offended at a lower rate than expected. Possible explanations for this finding are discussed.

Evaluation of the SORAG and the Static-99 on Belgian sex offenders committed to a forensic facility

This study evaluated the convergent and predictive validity of the Sex Offender Risk Appraisal Guide (SORAG; V. L. Quinsey, G. T. Harris, M. E. Rice, & C. A. Cormier, 1998) and the Static-99 (R. K. Hanson & D. Thornton, 1999, 2000) among 147 male sex offenders committed to a high-security hospital in Belgium (Centre de Défense Sociale "Les Marronniers"). Of the sample, 63.8% were child abusers (victims under 14 years of age), 24.6% were rapists (victims aged 14 years or more), and 11.5% were mixed-victim offenders (victims less than 14 years of age and victims aged 14 years or more). After an average follow-up period of 4.2 years (SD = 3.4 years), the sexual recidivism rate was 25.2%, the violent recidivism rate was 17.1%, and the general (any) recidivism rate was 33.1%. The SORAG and the Static-99 were moderately correlated with each other (r = .55), and both showed strong predictive validity for general and violent recidivism (ROC AUC's ranging from .68 to .72 for the total sample). Both instruments showed moderate predictive validity for sexual recidivism (AUC of .64 for SORAG and .66 for Static-99).

[Which cancerous diseases are significant for the risk assessment when underwriting life insurance?]

Cancer is the most important cause of death in life insurance and not cardiovascular disease! Life insurance is bought by persons aged between 15 and 65 years with an average of about 35 years. Therefore mortality statistics for the total population cannot be transferred to life insurance. In that segment cancer ranks before cardiovascular diseases. In females, cancer is even more important than in males because they are less prone to cardiovascular diseases in the age groups under consideration. Tumor mortality rises after age 40 and reaches its peak in males at age 70, in females the curve is moved towards higher ages and peaks at age 80.

Clinical-economic appropriateness of drug treatments: designing a method that combines evidence-based information and cost assessments to construct league tables accounting for the potential number of patients

This paper presents a method to assess drug treatment appropriateness, based on an original combination of economic analysis, pharmacoepidemiological techniques and evidence-based information. This method generates an index of clinical-economic appropriateness for the treatment under examination, by comparing the theoretically expected health gain (EHG) to the yearly national expenditure (EXPEND) on that drug and the amount of health that is thought to be gained in the 'real' patients (RHG). This paper reviews all the analyses conducted so far using this method, and discusses their main results. The primary aim of this article is to suggest a ranking approach for allocating the drug budgets of national health systems.

Conversion of mortality ratios to a numerical rating classification for life insurance underwriting-revisited

This is a commentary requested by the J Insur Med Editor to accompany a reprinting in this 2004 issue of my 1988 article on "Conversion of Mortality Ratios to a Numerical Rating Classification for Life Underwriting" (J Insur Med 1988;20:54-61). Topics discussed in this commentary include the distinction between short-term and long-term mortality follow-up in certain conditions, the format and the introductory text of the US Decennial Life Tables, the distinction between mortality rate and mortality probability, averaging mortality rates over a period of years, and the great value of the exemplary follow-up study used in the 1988 article.

Actuarial assessment of risk among sex offenders

The appraisal of risk among sex offenders has seen recent advances through the advent of actuarial assessments. Statistics derived from Relative Operating Characteristics (ROCs) permit the comparison of predictive accuracies achieved by different instruments even among samples that exhibit different base rates of recidivism. Such statistics cannot, however, solve problems introduced when items from actuarial tools are omitted, when reliability is low, or when there is high between-subject variability in the duration of the follow-up. We present empirical evidence suggesting that when comprehensive actuarial tools (VRAG and SORAG) are scored with high reliability, without missing items, and when samples of offenders have fixed and equal opportunity for recidivism, predictive accuracies are maximized near ROC areas of 0.90. Although the term "dynamic" has not been consistently defined, such accuracies leave little room for further improvement in long-term prediction by dynamic risk factors. We address the mistaken idea that long-term, static risk levels have little relevance for clinical intervention with sex offenders. We conclude that highly accurate prediction of violent criminal recidivism can be achieved by means of highly reliable and thorough scoring of comprehensive multi-item actuarial tools using historical items (at least until potent therapies are identified). The role of current moods, attitudes, insights, and physiological states in causing contemporaneous behavior notwithstanding, accurate prediction about which sex offenders will commit at least one subsequent violent offense can be accomplished using complete information about past conduct.

Sex offenders and actuarial risk assessments: ethical considerations

When assessing the recidivism risk of previously convicted sex offenders, the relevant ethical standards and practice guidelines obligate psychologists to acknowledge numerous limits related to their data and conclusions. For the actuarial instruments used in these assessments, the highest rates of classification accuracy are associated with greater specificity compared with sensitivity. Selecting cut-off scores to maximize sensitivity results in an inordinate frequency of false positive classifications. Attempts at maximizing specificity create an undesirable frequency of false negative classifications.Unfortunately, adjusted actuarial assessment cannot remedy these problems created by the sensitivity-specificity tradeoff. As an unstandardized procedure, the accuracy of adjusted actuarial assessment is severely limited. Consequently, civil proceedings for previously convicted sexual offenders rely on assessments of very limited accuracy. Undertaking these assessments, therefore, may be inconsistent with relevant ethical standards and practice guidelines.

Risk factors for ill health insurance claims

OBJECTIVES

This study examined the information available at application for income protection insurance, to determine if any factors were predictive of a claim. The strength and significance of such factors were assessed and a predictive model was developed.

BACKGROUND

The factors underlying life assurance risks are well known, but this is not the case for income protection insurance. For accurate underwriting of income protection insurance, it is important to know what information available at application has power to predict a claim. Improving the scientific accuracy of underwriting is good business practice, as well as answering the demands of disability legislation.

METHODS

We studied all data available at application for 959 current claimants and 1417 non-claimants, using a case-control study design. Information included applicants' description of their occupation, marital status, build and habits, plus a questionnaire asking about their personal health. For some applicants medical reports were available as well. Information was transcribed onto a database, and univariate and multivariate analyses were performed. A predictive scoring system was established and its performance measured by receiver operating characteristic curves.

RESULTS

Significant associations with claiming were found for many variables, including age (odds-ratio 1.04, p < 0.001), height (0.11, p = 0.03), smoking (2.10, p < 0.001), abstinence from alcohol (1.56, p = 0.01), recent medical advice (1.34, p = 0.06), and having had a lower gastrointestinal disorder (1.51, p = 0.04). Using all the information from the application, a predictive model was constructed. This model had good predictive power with an area under the receiver operating characteristic curve of 72%.

CONCLUSIONS

Classical underwriting factors were generally shown to have predictive power for income protection insurance. The predictive scoring strengthens the scientific basis for underwriting and could be developed to simplify and expedite the underwriting process.

Actuarial assessment of sex offender recidivism risk: a cross-validation of the RRASOR and the Static-99 in Sweden

We cross-validated two actuarial risk assessment tools, the RRASOR (R. K. Hanson, 1997) and the Static-99 (R. K. Hanson & D. Thornton, 1999), in a retrospective follow-up (mean follow-up time = 3.69 years) of all sex offenders released from Swedish prisons during 1993-1997 (N = 1,400, all men, age > or =18 years). File-based data were collected by a researcher blind to the outcome (registered criminal recidivism), and individual risk factors as well as complete instrument characteristics were explored. Both the RRASOR and the Static-99 showed similar and moderate predictive accuracy for sexual reconvictions whereas the Static-99 exhibited a significantly higher accuracy for the prediction of any violent recidivism as compared to the RRASOR. Although particularly the Static-99 proved moderately robust as an actuarial measure of recidivism risk among sexual offenders in Sweden, both procedures may need further evaluation, for example, with sex offender subpopulations differing ethnically or with respect to offense characteristics. The usefulness of actuarial methods for the assessment of sex offender recidivism risk is discussed in the context of current practice.

Long-term care insurance underwriting: understanding eventual claims experience

Little is known about the accuracy of medical underwriting for long-term care insurance. The lack of data on claims experience continues to be an obstacle in testing the ability of medical underwriting to identify above average financial risks. This study used actual claims data to simulate medical underwriting and to examine the risk, duration, and timing of nursing home use for people with conditions that are uninsurable. The results show that at least one older person in seven who is rejected for long-term care insurance due to underwriting may not represent greater financial risk to insurers than do those who are accepted.

Developing a clinically useful actuarial tool for assessing violence risk

BACKGROUND

A new actuarial method for violence risk assessment--the Iterative Classification Tree (ICT)--has become available. It has a high degree of accuracy but can be time and resource intensive to administer.

AIMS

To increase the clinical utility of the ICT method by restricting the risk factors used to generate the actuarial tool to those commonly available in hospital records or capable of being routinely assessed in clinical practice.

METHOD

A total of 939 male and female civil psychiatric patients between 18 and 40 years old were assessed on 106 risk factors in the hospital and monitored for violence to others during the first 20 weeks after discharge.

RESULTS

The ICT classified 72.6% of the sample as either low risk (less than half of the sample's base rate of violence) or high risk (more than twice the sample's base rate of violence).

CONCLUSIONS

A clinically useful actuarial method exists to assist in violence risk assessment.

Parametric cure models of relative and cause-specific survival for grouped survival times

With parametric cure models, we can express survival parameters (e.g. cured fraction, location and scale parameters) as functions of covariates. These models can measure survival from a specific disease process, either by examining deaths due to the cause under study (cause-specific survival), or by comparing all deaths to those in a matched control population (relative survival). We present a binomial maximum likelihood algorithm to be used for actuarial data, where follow-up times are grouped into specific intervals. Our algorithm provides simultaneous maximum likelihood estimates for all the parameters of a cure model and can be used for cause-specific or relative survival analysis with a variety of survival distributions. Current software does not provide the flexibility of this unified approach.

Improving risk assessments for sex offenders: a comparison of three actuarial scales

The study compared the predictive accuracy of three sex offender risk-assessment measures: the RRASOR (Hanson, 1997), Thornton's SACJ-Min (Grubin, 1998), and a new scale, Static-99, created by combining the items from the RRASOR and SACJ-Min. Predictive accuracy was tested using four diverse datasets drawn from Canada and the United Kingdom (total n = 1301). The RRASOR and the SACJ-Min showed roughly equivalent predictive accuracy, and the combination of the two scales was more accurate than either original scale. Static-99 showed moderate predictive accuracy for both sexual recidivism (r = 0.33, ROC area = 0.71) and violent (including sexual) recidivism (r = 0.32, ROC area = 0.69). The variation in the predictive accuracy of Static-99 across the four samples was no more than would be expected by chance.

A classification tree approach to the development of actuarial violence risk assessment tools

Since the 1970s, a wide body of research has suggested that the accuracy of clinical risk assessments of violence might be increased if clinicians used actuarial tools. Despite considerable progress in recent years in the development of such tools for violence risk assessment, they remain primarily research instruments, largely ignored in daily clinical practice. We argue that because most existing actuarial tools are based on a main effects regression approach, they do not adequately reflect the contingent nature of the clinical assessment processes. To enhance the use of actuarial violence risk assessment tools, we propose a classification tree rather than a main effects regression approach. In addition, we suggest that by employing two decision thresholds for identifying high- and low-risk cases--instead of the standard single threshold--the use of actuarial tools to make dichotomous risk classification decisions may be further enhanced. These claims are supported with empirical data from the MacArthur Violence Risk Assessment Study.

End points in the analysis of breast cancer survival: relapse versus death from tumor

BACKGROUND

To determine whether relapse and death from tumor are comparable as survival end points for assessing therapeutic efficacy, five prospective, randomized clinical trials of adjuvant therapy for stage II breast cancer were analyzed. One thousand eight hundred ninety patients were combined from five clinical groups into a single group for analysis.

METHODS

Actuarial and parametric survival methods were used to generate three estimates for the likelihood of cure (LOC): (1) for all patients, with relapse as the end point to survival (LOCR); (2) for all patients, with death from tumor as the end point (LOCD); and (3) for patients with relapse only with death from tumor as the end point (LOCRD). Linear regression analysis was used to compare time to relapse for each patient with time from relapse to death.

RESULTS

Estimates of LOCR ranged from 33.5% to 38.4%, estimates of LOCD ranged from 36.3% to 44.2%, and estimates of LOCRD ranged from 0% to 6%. Thus LOCR and LOCD are approximately equal for these patients. On the other hand, time to relapse correlated poorly with time from relapse to death (r2 = 0.005).

CONCLUSIONS

If therapy affects LOC, relapse and death should ultimately lead to the same conclusion with respect to therapeutic efficacy, because both end points lead to essentially the same LOC. If therapy affects time to relapse, however, these two end points may ultimately lead to different conclusions, because time to relapse correlates poorly with time from relapse to death.

Increasing prostate-specific antigen profile following definitive radiation therapy for localized prostate cancer: clinical observations

PURPOSE

To examine the natural history of patients who have received definitive radiation therapy alone for clinically localized prostate cancer and have an increasing prostate-specific antigen (PSA) profile.

PATIENTS AND METHODS

One hundred fifty-one men with an increasing PSA profile after definitive radiotherapy were identified. The subsequent natural history of these men, including local recurrence, distant metastasis, and survival, was examined. In 119 men, posttreatment PSA doubling times (PSADT) were calculated using linear regression. Cox regression models were used to examine the effect of clinical and treatment variables on clinical failure and survival.

RESULTS

Patients with high pretreatment PSA values, high Gleason scores, and T3 tumors were more likely to develop a PSA elevation. The median calculated post-treatment PSADT was 13 months, and 95% of patients had posttreatment PSADT of less than 3 years. PSADT was correlated with tumor stage and Gleason score. Five years after PSA elevation, the estimated rate of clinical local recurrence is 26% and the estimated rate of distant metastases is 47%. Rapid PSADT (< 12 months) and a short interval from the end of treatment to PSA elevation (< 12 months) were significant independent predictors of distant metastases. The estimated rates of overall and cause-specific survival 5 years after PSA elevation are 65% and 76%, respectively. Gleason grade is the only significant independent predictor of overall and cause-specific survival after PSA elevation.

CONCLUSION

The natural history of men who have an increasing PSA profile following definitive radiotherapy is heterogeneous. In the absence of salvage therapy, at least three quarters of men will have clinical evidence of recurrent disease 5 years after a PSA elevation is detected. Men with a rapid posttreatment PSADT and a short interval from the end of treatment to an increasing PSA profile are at a very high risk of developing distant metastasis within 5 years of PSA elevation.

Using actuarial models to assess managed care risk

Actuarial models can be used to illustrate the financial risks inherent in healthcare provider operations. They are especially useful in analyzing the implications of managed care agreements, which revolve around risk and the financing of risk. Simple actuarial models may focus on inpatient utilization and reimbursement under capitation. More sophisticated models detail risks associated with individual diagnosis-related groups, as well as with many types of outpatient and physician services. Actuarial models can provide an objective basis for planning for the future and can be used to build consensus on strategies that will ensure success under managed care agreements.

[The characteristics of actuarial calculations for voluntary medical insurance]

Presents methods of mathematical validation of agreements on voluntary medical insurance. Reduction coefficients are used for determining the onset of the insurer's responsibility after a certain number of invalidity days. The reduction coefficient is regarded as a probability that the insured person recovers not later than by a certain date, and the sequence of these coefficients as function of distribution of the course of invalidity. Use of the actuarial estimations for validating different aspects of voluntary medical insurance helps specify the probable payments and provide the financial stability of insurance companies.

Risk adjusting community rated health plan premiums: a survey of risk assessment literature and policy applications

This paper surveys recent health care reform debates and empirical evidence regarding the potential role for risk adjusters in addressing the problem of competitive risk segmentation under capitated financing. We discuss features of health plan markets affecting risk selection, methodological considerations in measuring it, and alternative approaches to financial correction for risk differentials. The appropriate approach to assessing risk differences between health plans depends upon the nature of market risk selection allowed under a given reform scenario. Because per capita costs depend on a health plan's population risk, efficiency, and quality of service, risk adjustment will most strongly promote efficiency in environments with commensurately strong incentives for quality care.

Pitfalls of inferring annual mortality from inspection of published survival curves

In many FU articles currently published, results are given primarily in the form of graphs of survival curves, rather than in the form of life table data. Sometimes the authors may comment on the slope of the survival curve as though it were equal to the annual mortality rate (after reversal of the minus sign to a plus sign). Even if no comment of this sort is made, medical directors and underwriters may be tempted to think along similar lines in trying to interpret the significance of the survival curve in terms of mortality. However it is a very serious error of life table methodology to conceive of mortality rate as equal to the negative slope of the survival curve. The nature of the error is demonstrated in this article. An annual mortality rate derived from the survival curve actually depends on two variables: a quotient with the negative slope (sign reversed), delta P/ delta as the numerator, and the survival rate, P, itself as the denominator. The implications of this relationship are discussed. If there are two "parallel" survival curves with the same slope at a given time duration, the lower curve will have a higher mortality rate than the upper curve. A constant slope with increasing duration means that the annual mortality rate also increases with duration. Some characteristics of high initial mortality are also discussed and their relation to different units of FU time.(ABSTRACT TRUNCATED AT 250 WORDS)

Improved methodology for analyzing local and distant recurrence

Studies of radiation therapy and/or surgery in the treatment of cancer frequently use actuarial methods to estimate curves of time to local failure and compare two such curves with statistical methods originally developed for survival data. In such analyses, patients who fail first in distant sites or die before local failure are considered censored for time to local failure. While the arithmetic of these calculations is usually correct, the interpretation of the results is almost universally incorrect. For example, an actuarial Kaplan-Meier curve of time to breast recurrence after breast conserving treatment consistently overestimates the percentage of patients who would benefit from a subsequent mastectomy. Actuarial methods require the assumption that time to local failure and time to distant failure are statistically independent. For most human malignancies this is not a reasonable assumption, since there are always some patient subgroups at high risk of both local and distant failure and some patient subgroups at low risk for either type of failure. Without the assumption of independence, the time to local failure distribution is not well defined. The basic problem is that estimating time to local failure falls into the category of analyzing "competing risks," since the various causes of failure are competing for the same patient. For this reason, the effects of a particular treatment on local failure cannot be assessed separately from its effects on distant failure. This report explains the concepts of statistical independence, nonidentifiability, and competing risks and illustrates the pitfalls of using actuarial methods to assess local tumor control.(ABSTRACT TRUNCATED AT 250 WORDS)

Life-span of amalgam restorations in primary molars: some results and comments on statistical analyses

The life-span of amalgam restorations placed in primary molars by three general dental practitioners is investigated. Two methods of analysis have been carried out. In the analysis of "non-independent" restorations (i.e. using several restorations from each mouth), the median survival time was 52.8 months with an apparent standard error of 2.1 months. In the analysis of "independent" restorations (i.e. only using one restoration from each mouth), three random samples were chosen and their median survival times were 68.2 months (s.e. = 6.9), 60.5 months (s.e. = 6.9), and 56.8 months (s.e. = 3.7). The two methods are compared and discussed. It is concluded that the analysis of "independent" restorations should be the method of choice in studying the life-span of restorations.

Physicians who have lost their malpractice insurance. Their demographic characteristics and the surplus-lines companies that insure them

The present study analyzes demographic data on 920 physicians who lost their coverage and applied to a "surplus-lines" company that insures essentially all applicants. Our analysis reveals that (1) some specialties are heavily overrepresented in the surplus-lines pool, (2) physicians aged 45 to 54 years are also overrepresented, (3) board certification is seen as frequently in the surplus-lines group as in the US physician population, and (4) the percentage of foreign medical graduates in the surplus-lines pool is virtually the same as that in the US physician population. A model of the actuarial process by which claims data can lead to termination of standard coverage suggests that disproportionate representation of high-risk specialties is not simply a function of a high average claims rate. We also show that, in contrast to joint underwriting associations, surplus-lines companies impose high premiums, large deductibles, and restrictions on practice, all of which are likely to reduce the frequency of negligent behavior.