Frailty modeling of bimodal age-incidence curves of nasopharyngeal carcinoma in low-risk populations

The Correlation between Risk Factors and Epstein-Barr Virus Serum Antibody with Histopathological Typing of Nasopharyngeal Carcinoma

BACKGROUND: The risk-combination of genetic or familial history, environmental risk factors, and EBV infection might cause nasopharyngeal carcinogenesis. The serum antibody for EBV IgA, namely, EBNA1+VCA-p18 has a good sensitivity as an early diagnostic test for nasopharyngeal carcinoma (NPC). AIM: This study aims to determine the correlation between risk factors and histopathological typing of NPC and also the correlation between the IgA [EBNA-1 + VCA p-18] ELISA and histologic type. METHODS: A cross-sectional method was used on 108 NPC patients which filled a questionnaire through an in-depth interview on the family condition to cancer, habit/lifestyle, and environmental risks. A total of 47 subjects were willing to donate blood samples for IgA [EBNA1 + VCA p-18] ELISA. Furthermore, Kendall’s tau-b (τ) correlation test was performed on NPC keratin type (WHO-1) and non-keratin (WHO-2 and 3). RESULTS: The results showed that the family history of non-keratinized NPC was associated with NPC WHO-3 as demonstrated by τ = 0.473, as well as salt-eating with τ = 0.334, smoked/grilled fish/meat eating τ = 0.205, instant noodle-eating τ = 0.356, consuming canned/packaged canned foods τ = 0.240, and flavored food eating habits τ = 0.364, along with passive smoking τ = 0.377, and chronic nasopharyngeal infection τ = 0.530. The IgA titers, namely, [EBNA1 + VCA p-18] ELISA for non-keratin type NPC was greater than the keratin type; however, it was not related to WHO-3 NPC as indicated by τ = 0.376, and p = 0.011 put this underlying before however. CONCLUSIONS: The positivity of IgA [EBNA-1 + VCA p-18] ELISA does not correlate with the non-keratin type histologic NPC, family history, as well as salt-eating, instant noodle, and flavored food eating habits, along with passive smoking and nasopharyngeal infection.

Rare tumors: Retinoblastoma, nasopharyngeal cancer, and adrenocorticoid tumors

The role of surgery, chemotherapy, and radiation therapy for retinoblastoma has evolved considerably over the years with the efficacy of intraarterial chemotherapy and the high incidence of secondary malignant neoplasms following radiation therapy. The use of spot scanning intensity-modulated proton therapy may reduce the risk of secondary malignancies. For pediatric nasopharyngeal carcinoma, the current standard of care is induction chemotherapy followed by chemoradiation therapy. For adrenocortical carcinoma, the mainstay of treatment is surgery and chemotherapy. The role of radiation therapy remains to be defined.

Prostate-specific antigen testing for prostate cancer: Depleting a limited pool of susceptible individuals?

After the introduction of the prostate specific antigen (PSA) test in the 1980s, a sharp increase in the incidence rate of prostate cancer was seen in the United States. The age-specific incidence patterns exhibited remarkable shifts to younger ages, and declining rates were observed at old ages. Similar trends were seen in Norway. We investigate whether these features could, in combination with PSA testing, be explained by a varying degree of susceptibility to prostate cancer in the populations. We analyzed incidence data from the United States' Surveillance, Epidemiology, and End Results program for 1973-2010, comprising 511,027 prostate cancers in men ≥40 years old, and Norwegian national incidence data for 1953-2011, comprising 113,837 prostate cancers in men ≥50 years old. We developed a frailty model where only a proportion of the population could develop prostate cancer, and where the increased risk of diagnosis due to the massive use of PSA testing was modelled by encompassing this heterogeneity in risk. The frailty model fits the observed data well, and captures the changing age-specific incidence patterns across birth cohorts. The susceptible proportion of men is [Formula: see text] in the United States and [Formula: see text] in Norway. Cumulative incidence rates at old age are unchanged across birth cohort exposed to PSA testing at younger and younger ages. The peaking cohort-specific age-incidence curves of prostate cancer may be explained by the underlying heterogeneity in prostate cancer risk. The introduction of the PSA test has led to a larger number of diagnosed men. However, no more cases are being diagnosed in total in birth cohorts exposed to the PSA era at younger and younger ages, even though they are diagnosed at younger ages. Together with the earlier peak in the age-incidence curves for younger cohorts, and the strong familial association of the cancer, this constitutes convincing evidence that the PSA test has led to a higher proportion, and an earlier timing, of diagnoses in a limited pool of susceptible individuals.

Tumor dormancy and frailty models: A novel approach

Frailty models are here proposed in the tumor dormancy framework, in order to account for possible unobservable dependence mechanisms in cancer studies where a non-negligible proportion of cancer patients relapses years or decades after surgical removal of the primary tumor. Relapses do not seem to follow a memory-less process, since their timing distribution leads to multimodal hazards. From a biomedical perspective, this behavior may be explained by tumor dormancy, i.e., for some patients microscopic tumor foci may remain asymptomatic for a prolonged time interval and, when they escape from dormancy, micrometastatic growth results in a clinical disease appearance. The activation of the growth phase at different metastatic states would explain the occurrence of metastatic recurrences and mortality at different times (multimodal hazard). We propose a new frailty model which includes in the risk function a random source of heterogeneity (frailty variable) affecting the components of the hazard function. Thus, the individual hazard rate results as the product of a random frailty variable and the sum of basic hazard rates. In tumor dormancy, the basic hazard rates correspond to micrometastatic developments starting from different initial states. The frailty variable represents the heterogeneity among patients with respect to relapse, which might be related to unknown mechanisms that regulate tumor dormancy. We use our model to estimate the overall survival in a large breast cancer dataset, showing how this improves the understanding of the underlying biological process.

Understanding variation in disease risk: the elusive concept of frailty

The concept of frailty plays a major role in the statistical field of survival analysis. Frailty variation refers to differences in risk between individuals which go beyond known or measured risk factors. In other words, frailty variation is unobserved heterogeneity. Although understanding frailty is of interest in its own right, the literature on survival analysis has demonstrated that existence of frailty variation can lead to surprising artefacts in statistical estimation that are important to examine. We present literature that demonstrates the presence and significance of frailty variation between individuals. We discuss the practical content of frailty variation, and show the link between frailty and biological concepts like (epi)genetics and heterogeneity in disease risk. There are numerous suggestions in the literature that a good deal of this variation may be due to randomness, in addition to genetic and/or environmental factors. Heterogeneity often manifests itself as clustering of cases in families more than would be expected by chance. We emphasize that apparently moderate familial relative risks can only be explained by strong underlying variation in disease risk between families and individuals. Finally, we highlight the potential impact of frailty variation in the interpretation of standard epidemiological measures such as hazard and incidence rates.

A hierarchical frailty model for familial testicular germ-cell tumors

Using a 2-level hierarchical frailty model, we analyzed population-wide data on testicular germ-cell tumor (TGCT) status in 1,135,320 two-generational Norwegian families to examine the risk of TGCT in family members of patients. Follow-up extended from 1954 (cases) or 1960 (unaffected persons) to 2008. The first-level frailty variable was compound Poisson-distributed. The underlying Poisson parameter was randomized to model the frailty variation between families and was decomposed additively to characterize the correlation structure within a family. The frailty relative risk (FRR) for a son, given a diseased father, was 4.03 (95% confidence interval (CI): 3.12, 5.19), with a borderline significantly higher FRR for nonseminoma than for seminoma (P = 0.06). Given 1 affected brother, the lifetime FRR was 5.88 (95% CI: 4.70, 7.36), with no difference between subtypes. Given 2 affected brothers, the FRR was 21.71 (95% CI: 8.93, 52.76). These estimates decreased with the number of additional healthy brothers. The estimated FRRs support previous findings. However, the present hierarchical frailty approach allows for a very precise definition of familial risk. These FRRs, estimated according to numbers of affected/nonaffected family members, provide new insight into familial TGCT. Furthermore, new light is shed on the different familial risks of seminoma and nonseminoma.

Schizophrenia susceptibility and age of diagnosis--a frailty approach

BACKGROUND

Using a frailty model approach, we aim to evaluate the effect of early-life risk factors on susceptibility and age at diagnosis of schizophrenia. We assume paternal age and familial schizophrenia influence the susceptibility, while these and several early risk factors influence the age of diagnosis.

METHOD

Schizophrenia incidence data were derived from the population-based Swedish Patient Registry; including individuals aged 18 to 45 years, diagnosed between 1974 and 2008. Data were analyzed by a frailty model, a random effects model in survival analysis, using a compound Poisson model.

RESULTS

15,340 incident schizophrenia cases were included. For individuals without familial schizophrenia, a protective effect was seen across most ages of diagnosis for females, low paternal age, born in rural areas, and being born in later cohorts. For individuals with familial schizophrenia, a protective effect is found for females diagnosed between ages 18 and 30 years, corresponding values were 18-25 years for low paternal age. Being born in rural areas and in the last birth cohort was protective for all. The estimated proportion of susceptible was 5% for those without familial schizophrenia and 18% for individuals with familial schizophrenia. There was no statistically significant effect of paternal age on the proportion of susceptible.

DISCUSSION

To our knowledge, this is the first regression modeling of time to schizophrenia diagnosis allowing for a non-susceptible fraction of the population, including age dependent modeling of covariate effects and an interaction. Applying frailty model to schizophrenia provide etiological clues, elucidating patterns of susceptibility and age-at-diagnosis for which early-life factors are of importance.

Frailty modeling of age-incidence curves of osteosarcoma and Ewing sarcoma among individuals younger than 40 years

The Armitage-Doll model with random frailty can fail to describe incidence rates of rare cancers influenced by an accelerated biological mechanism at some, possibly short, period of life. We propose a new model to account for this influence. Osteosarcoma and Ewing sarcoma are primary bone cancers with characteristic age-incidence patterns that peak in adolescence. We analyze Surveillance, Epidemiology and End Result program incidence data for whites younger than 40 years diagnosed during the period 1975-2005, with an Armitage-Doll model with compound Poisson frailty. A new model treating the adolescent growth spurt as the accelerated mechanism affecting cancer development is a significant improvement over that model. We also model the incidence rate conditioning on the event of having developed the cancers before the age of 40 years and compare the results with those predicted by the Armitage-Doll model. Our results support existing evidence of an underlying susceptibility for the two cancers among a very small proportion of the population. In addition, the modeling results suggest that susceptible individuals with a rapid growth spurt acquire the cancers sooner than they otherwise would have if their growth had been slower. The new model is suitable for modeling incidence rates of rare diseases influenced by an accelerated biological mechanism.

Frailty modeling of the bimodal age-incidence of Hodgkin lymphoma in the Nordic countries

BACKGROUND

The bimodality of the age-incidence curve of Hodgkin lymphoma (HL) has been ascribed to the existence of subgroups with distinct etiologies. Frailty models can be usefully applied to age-incidence curves of cancer to aid the understanding of biological phenomena in these instances. The models imply that for a given disease, a minority of individuals are at high risk, compared with the low-risk majority.

METHODS

Frailty modeling is applied to interpret HL incidence on the basis of population-based cancer registry data from the five Nordic countries for the period 1993 to 2007. There were a total of 8,045 incident cases and 362,843,875 person-years at risk in the study period.

RESULTS

A bimodal frailty analysis provides a reasonable fit to the age-incidence curves, employing 2 prototype models, which differ by having the sex covariate included in the frailty component (model 1) or in the baseline Weibull hazard (model 2). Model 2 seemed to fit better with our current understanding of HL than model 1 for the male-to-female ratio, number of rate-limiting steps in the carcinogenic process, and proportion of susceptibles; whereas model 1 performed better related to the heterogeneity in HL among elderly males.

CONCLUSION

The present analysis shows that HL age-incidence data are consistent with a bimodal frailty model, indicating that heterogeneity in cancer susceptibility may give rise to bimodality at the population level, although the individual risk remains simple and monotonically increasing by age.

IMPACT

Frailty modeling adds to the existing body of knowledge on the heterogeneity in risk of acquiring HL.