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Article ; Online: Weighting estimation in the cause-specific Cox regression with partially missing causes of failure.

Lee, Jooyoung / Ogino, Shuji / Wang, Molin

2024

Abstract: Complex diseases are often analyzed using disease subtypes classified by multiple biomarkers to study pathogenic heterogeneity. In such molecular pathological epidemiology research, we consider a weighted Cox proportional hazard model to evaluate the ... ...

Abstract	Complex diseases are often analyzed using disease subtypes classified by multiple biomarkers to study pathogenic heterogeneity. In such molecular pathological epidemiology research, we consider a weighted Cox proportional hazard model to evaluate the effect of exposures on various disease subtypes under competing-risk settings in the presence of partially or completely missing biomarkers. The asymptotic properties of the inverse and augmented inverse probability-weighted estimating equation methods are studied with a general pattern of missing data. Simulation studies have been conducted to demonstrate the double robustness of the estimators. For illustration, we applied this method to examine the association between pack-years of smoking before the age of 30 and the incidence of colorectal cancer subtypes defined by a combination of four tumor molecular biomarkers (statuses of microsatellite instability, CpG island methylator phenotype, BRAF mutation, and KRAS mutation) in the Nurses' Health Study cohort.
Language	English
Publishing date	2024-04-24
Publishing country	England
Document type	Journal Article
ZDB-ID	843037-8
ISSN	1097-0258 ; 0277-6715
ISSN (online)	1097-0258
ISSN	0277-6715
DOI	10.1002/sim.10084
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Article ; Online: Comparison between inverse-probability weighting and multiple imputation in Cox model with missing failure subtype.

Guo, Fuyu / Langworthy, Benjamin / Ogino, Shuji / Wang, Molin

Statistical methods in medical research

2024 Volume 33, Issue 2, Page(s) 344–356

Abstract: Identifying and distinguishing risk factors for heterogeneous disease subtypes has been of great interest. However, missingness in disease subtypes is a common problem in those data analyses. Several methods have been proposed to deal with the missing ... ...

Abstract	Identifying and distinguishing risk factors for heterogeneous disease subtypes has been of great interest. However, missingness in disease subtypes is a common problem in those data analyses. Several methods have been proposed to deal with the missing data, including complete-case analysis, inverse-probability weighting, and multiple imputation. Although extant literature has compared these methods in missing problems, none has focused on the competing risk setting. In this paper, we discuss the assumptions required when complete-case analysis, inverse-probability weighting, and multiple imputation are used to deal with the missing failure subtype problem, focusing on how to implement these methods under various realistic scenarios in competing risk settings. Besides, we compare these three methods regarding their biases, efficiency, and robustness to model misspecifications using simulation studies. Our results show that complete-case analysis can be seriously biased when the missing completely at random assumption does not hold. Inverse-probability weighting and multiple imputation estimators are valid when we correctly specify the corresponding models for missingness and for imputation, and multiple imputation typically shows higher efficiency than inverse-probability weighting. However, in real-world studies, building imputation models for the missing subtypes can be more challenging than building missingness models. In that case, inverse-probability weighting could be preferred for its easy usage. We also propose two automated model selection procedures and demonstrate their usage in a study of the association between smoking and colorectal cancer subtypes in the Nurses' Health Study and Health Professional Follow-Up Study.
MeSH term(s)	Humans ; Proportional Hazards Models ; Models, Statistical ; Follow-Up Studies ; Data Interpretation, Statistical ; Probability ; Computer Simulation ; Risk Factors
Language	English
Publishing date	2024-01-23
Publishing country	England
Document type	Journal Article
ZDB-ID	1136948-6
ISSN	1477-0334 ; 0962-2802
ISSN (online)	1477-0334
ISSN	0962-2802
DOI	10.1177/09622802231226328
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Zs.A 3564: Show issues

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Article ; Online: Fusobacteria alterations are associated with colorectal cancer liver metastasis and a poor prognosis.

Jin, Min / Fan, Qilin / Shang, Fumei / Zhang, Tao / Ogino, Shuji / Liu, Hongli

Oncology letters

2024 Volume 27, Issue 5, Page(s) 235

Abstract: Liver metastasis is a major cause of mortality in patients with advanced stages of colorectal cancer (CRC). The gut microbiota has been demonstrated to influence the progression of liver diseases, potentially providing novel perspectives for diagnosis, ... ...

Abstract	Liver metastasis is a major cause of mortality in patients with advanced stages of colorectal cancer (CRC). The gut microbiota has been demonstrated to influence the progression of liver diseases, potentially providing novel perspectives for diagnosis, treatment and research. However, the gut microbial characteristics in CRC with liver metastasis (LM) and with no liver metastasis (NLM) have not yet been fully established. In the present study, high-throughput 16S RNA sequencing technology was employed, in order to examine the gut microbial richness and composition in patients with CRC with LM or NLM. A discovery cohort (cohort 2; LM=18; NLM=36) and a validation cohort (cohort 3; LM=13; NLM=41) were established using fresh feces. In addition, primary carcinoma tissue samples were also analyzed (LM=8 and NLM=10) as a supplementary discovery cohort (cohort 1). The findings of the present study indicated that the intestinal microbiota richness and diversity were increased in the LM group as compared to the NLM group. A significant difference was observed in species composition between the LM and NLM group. In the two discovery cohorts with two different samples, the dominant phyla were consistent, but varied at lower taxonomic levels. Phylum Fusobacteria presented consistent and significant enrichment in LM group in both discovery cohorts. Furthermore, with the application of a random forest model and receiver operator characteristic curve analysis, Fusobacteria was identified as a potential biomarker for LM. Moreover, Fusobacteria was also a poor prognosis factor for survival. Importantly, the findings were reconfirmed in the validation cohort. On the whole, the findings of the present study demonstrated that CRC with LM and NLM exhibit distinct gut microbiota characteristics. Fusobacteria detection thus has potential for use in predicting LM and a poor prognosis of patients with CRC.
Language	English
Publishing date	2024-03-26
Publishing country	Greece
Document type	Journal Article
ZDB-ID	2573196-8
ISSN	1792-1082 ; 1792-1074
ISSN (online)	1792-1082
ISSN	1792-1074
DOI	10.3892/ol.2024.14368
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Article ; Online: The Prevalence and Prognosis of Microsatellite Instability-High/Mismatch Repair-Deficient Colorectal Adenocarcinomas in the United States.

Gutierrez, Catherine / Ogino, Shuji / Meyerhardt, Jeffrey A / Iorgulescu, J Bryan

JCO precision oncology

2023 Volume 7, Page(s) e2200179

Abstract: Purpose: Microsatellite instability (MSI) and DNA mismatch repair (MMR) status is an indispensable biomarker in the management of colorectal cancers. We therefore examined the epidemiology of MSI-high/MMR-deficient colorectal cancers in the United ... ...

Abstract	Purpose: Microsatellite instability (MSI) and DNA mismatch repair (MMR) status is an indispensable biomarker in the management of colorectal cancers. We therefore examined the epidemiology of MSI-high/MMR-deficient colorectal cancers in the United States. Methods: Adults presenting with colorectal adenocarcinoma in 2018-2019 were identified from the US National Cancer Database. Attributes associated with MSI-high/MMR-deficiency were identified using multivariable logistic regression and reported using average adjusted probabilities (% Results: Among 101,259 colorectal adenocarcinomas in 2018-2019, 82.0% were microsatellite stable/MMR-proficient, 3.8% MSI-low, and 14.2% MSI-high/MMR-deficient-including 16.6%, 19.9%, 12.4%, and 7.3% of stage I, II, III, and IV cancers, respectively. In locoregional cancers, MSI-high/MMR-deficiency was associated with a bimodal age distribution, female sex, right-sided colonic origin, wild-type Conclusion: Our findings establish the epidemiology, features, and prognostic implications of MSI-high/MMR-deficiency among colorectal adenocarcinoma patients in the United States.
MeSH term(s)	Adult ; Humans ; Female ; United States/epidemiology ; Microsatellite Instability ; DNA Mismatch Repair/genetics ; Prevalence ; Colorectal Neoplasms/epidemiology ; Colorectal Neoplasms/genetics ; Prognosis ; Colonic Neoplasms/genetics ; Adenocarcinoma/epidemiology ; Adenocarcinoma/genetics
Language	English
Publishing date	2023-01-18
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ISSN	2473-4284
ISSN (online)	2473-4284
DOI	10.1200/PO.22.00179
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Article ; Online: The Cancer Spectrum Theory.

Lee, Hwa-Young / Song, Minkyo / Stopsack, Konrad H / Peng, Cheng / Phipps, Amanda I / Wang, Molin / Ogino, Shuji / Sasamoto, Naoko / Ugai, Tomotaka

Cancer discovery

2024 Volume 14, Issue 4, Page(s) 589–593

Abstract: Summary: Biological characteristics of tumors are heterogeneous, forming spectra in terms of several factors such as age at onset, anatomic spatial localization, tumor subtyping, and the degree of tumor aggressiveness (encompassing a neoplastic property ...

Abstract	Summary: Biological characteristics of tumors are heterogeneous, forming spectra in terms of several factors such as age at onset, anatomic spatial localization, tumor subtyping, and the degree of tumor aggressiveness (encompassing a neoplastic property spectrum). Instead of blindly using dichotomized approaches, the application of the multicategorical and continuous analysis approaches to detailed cancer spectrum data can contribute to a better understanding of the etiology of cancer, ultimately leading to effective prevention and precision oncology. We provide examples of cancer spectra and emphasize the importance of integrating the cancer spectrum theory into large-scale population cancer research.
MeSH term(s)	Humans ; Neoplasms/genetics ; Neoplasms/pathology ; Precision Medicine ; Medical Oncology
Language	English
Publishing date	2024-04-05
Publishing country	United States
Document type	Journal Article
ZDB-ID	2625242-9
ISSN	2159-8290 ; 2159-8274
ISSN (online)	2159-8290
ISSN	2159-8274
DOI	10.1158/2159-8290.CD-23-1494
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Zs.A 6916: Show issues

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Article ; Online: Mortality factors in pancreatic surgery: A systematic review. How important is the hospital volume?

Hunger, Richard / Seliger, Barbara / Ogino, Shuji / Mantke, Rene

International journal of surgery (London, England)

2022 Volume 101, Page(s) 106640

Abstract: Background: How the extent of confounding adjustment impact (hospital) volume-outcome relationships in published studies on pancreatic cancer surgery is unknown.: Methods: A systematic literature search was conducted for studies that investigated the ...

Abstract	Background: How the extent of confounding adjustment impact (hospital) volume-outcome relationships in published studies on pancreatic cancer surgery is unknown. Methods: A systematic literature search was conducted for studies that investigated the relationship between volume and outcome using a risk adjustment procedure by querying the following databases: PubMed, Cochrane Central Register of Controlled Trials, Livivo, Medline and the International Clinical Trials Registry Platform (last query: 2020/09/16). Importance of risk-adjusting covariates were assessed by effect size (odds ratio, OR) and statistical significance. The impact of covariate adjustment on hospital (or surgeon) volume effects was analyzed by regression and meta-regression models. Results: We identified 87 studies (75 based on administrative data) with nearly 1 million patients undergoing pancreatic surgery that included in total 71 covariates for risk adjustment. Of these, 33 (47%) had statistically significant effects on short-term mortality and 23 (32%) did not, while for 15 (21%) factors neither effect size nor statistical significance were reported. The most important covariates for short term mortality were patient-specific factors. Concerning the covariates, single comorbidities (OR: 4.6, 95% CI: 3.3 to 6.3) had the strongest impact on mortality followed by hospital volume (OR: 2.9, 95% CI: 2.5 to 3.3) and the procedure (OR: 2.2, 95% CI: 1.9 to 2.5). Among the single comorbidities, coagulopathy (OR: 4.5, 95% CI: 2.8 to 7.2) and dementia (OR: 4.2, 95% CI: 2.2 to 8.0) had the strongest influence on mortality. The regression analysis showed a significant decrease hospital volume effect with an increasing number of covariates considered (OR: 0.06, 95% CI: 0.10 to -0.03, P < 0.001), while such a relationship was not observed for surgeon volume (P = 0.35). Conclusions: This analysis demonstrated a significant inverse relationship between the extent of risk adjustment and the volume effect, suggesting the presence of unmeasured confounding and overestimation of volume effects. However, the conclusions are limited in that only the number of included covariates was considered, but not the effect size of the non-included covariates.
MeSH term(s)	Digestive System Surgical Procedures ; Hospital Mortality ; Hospitals ; Humans ; Odds Ratio ; Pancreatic Neoplasms ; Surgeons
Language	English
Publishing date	2022-05-04
Publishing country	United States
Document type	Journal Article ; Review ; Systematic Review
ZDB-ID	2212038-5
ISSN	1743-9159 ; 1743-9191
ISSN (online)	1743-9159
ISSN	1743-9191
DOI	10.1016/j.ijsu.2022.106640
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Zs.A 6502: Show issues

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Article ; Online: The microbiome and rise of early-onset cancers: knowledge gaps and research opportunities.

Mima, Kosuke / Hamada, Tsuyoshi / Inamura, Kentaro / Baba, Hideo / Ugai, Tomotaka / Ogino, Shuji

Gut microbes

2023 Volume 15, Issue 2, Page(s) 2269623

Abstract: Accumulating evidence indicates an alarming increase in the incidence of early-onset cancers, which are diagnosed among adults under 50 years of age, in the colorectum, esophagus, extrahepatic bile duct, gallbladder, liver, stomach, pancreas, as well as ... ...

Abstract	Accumulating evidence indicates an alarming increase in the incidence of early-onset cancers, which are diagnosed among adults under 50 years of age, in the colorectum, esophagus, extrahepatic bile duct, gallbladder, liver, stomach, pancreas, as well as the bone marrow (multiple myeloma), breast, head and neck, kidney, prostate, thyroid, and uterine corpus (endometrium). While the early-onset cancer studies have encompassed research on the wide variety of organs, this article focuses on research on digestive system cancers. While a minority of early-onset cancers in the digestive system are associated with cancer-predisposing high penetrance germline genetic variants, the majority of those cancers are sporadic and multifactorial. Although potential etiological roles of diets, lifestyle, environment, and the microbiome from early life to adulthood (i.e. in one's life course) have been hypothesized, exact contribution of each of these factors remains uncertain. Diets, lifestyle patterns, and environmental exposures have been shown to alter the oral and intestinal microbiome. To address the rising trend of early-onset cancers, transdisciplinary research approaches including lifecourse epidemiology and molecular pathological epidemiology frameworks, nutritional and environmental sciences, multi-omics technologies, etc. are needed. We review current evidence and discuss emerging research opportunities, which can improve our understanding of their etiologies and help us design better strategies for prevention and treatment to reduce the cancer burden in populations.
MeSH term(s)	Male ; Adult ; Female ; Humans ; Gastrointestinal Microbiome ; Neoplasms/epidemiology ; Neoplasms/etiology ; Neoplasms/therapy ; Incidence
Language	English
Publishing date	2023-10-30
Publishing country	United States
Document type	Journal Article ; Review ; Research Support, Non-U.S. Gov't
ZDB-ID	2575755-6
ISSN	1949-0984 ; 1949-0984
ISSN (online)	1949-0984
ISSN	1949-0984
DOI	10.1080/19490976.2023.2269623
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Article ; Online: Immunoscore for (colorectal) cancer precision medicine.

Ogino, Shuji / Giannakis, Marios

Lancet (London, England)

2018 Volume 391, Issue 10135, Page(s) 2084–2086

MeSH term(s)	CD8-Positive T-Lymphocytes ; Colonic Neoplasms ; Colorectal Neoplasms ; Humans ; Precision Medicine
Language	English
Publishing date	2018-05-10
Publishing country	England
Document type	Journal Article ; Comment
ZDB-ID	3306-6
ISSN	1474-547X ; 0023-7507 ; 0140-6736
ISSN (online)	1474-547X
ISSN	0023-7507 ; 0140-6736
DOI	10.1016/S0140-6736(18)30953-X
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Ua VI Zs.5: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular ab Jg. 2022: Lesesaal (EG)
Zs.MG 94: Show issues

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Article ; Online: Reflection on modern methods: causal inference considerations for heterogeneous disease etiology.

Nevo, Daniel / Ogino, Shuji / Wang, Molin

International journal of epidemiology

2021 Volume 50, Issue 3, Page(s) 1030–1037

Abstract: Molecular pathological epidemiology research provides information about pathogenic mechanisms. A common study goal is to evaluate whether the effects of risk factors on disease incidence vary between different disease subtypes. A popular approach to ... ...

Abstract	Molecular pathological epidemiology research provides information about pathogenic mechanisms. A common study goal is to evaluate whether the effects of risk factors on disease incidence vary between different disease subtypes. A popular approach to carrying out this type of research is to implement a multinomial regression in which each of the non-zero values corresponds to a bona fide disease subtype. Then, heterogeneity in the exposure effects across subtypes is examined by comparing the coefficients of the exposure between the different subtypes. In this paper, we explain why this common method potentially cannot recover causal effects, even when all confounders are measured, due to a particular type of selection bias. This bias can be explained by recognizing that the multinomial regression is equivalent to a series of logistic regressions; each compares cases of a certain subtype to the controls. We further explain how this bias arises using directed acyclic graphs and we demonstrate the potential magnitude of the bias by analysis of a hypothetical data set and by a simulation study.
MeSH term(s)	Bias ; Causality ; Confounding Factors, Epidemiologic ; Humans ; Logistic Models ; Selection Bias
Language	English
Publishing date	2021-01-22
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	187909-1
ISSN	1464-3685 ; 0300-5771
ISSN (online)	1464-3685
ISSN	0300-5771
DOI	10.1093/ije/dyaa278
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Zs.A 893: Show issues

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Article ; Online: Cancer as microenvironmental, systemic and environmental diseases: opportunity for transdisciplinary microbiomics science.

Inamura, Kentaro / Hamada, Tsuyoshi / Bullman, Susan / Ugai, Tomotaka / Yachida, Shinichi / Ogino, Shuji

Gut

2022

Abstract: Cancer is generally regarded as a localised disease, with the well-established role of the tumour microenvironment. However, the realm of cancer goes beyond the tumour microenvironment, and cancer should also be regarded as a systemic and environmental ... ...

Abstract	Cancer is generally regarded as a localised disease, with the well-established role of the tumour microenvironment. However, the realm of cancer goes beyond the tumour microenvironment, and cancer should also be regarded as a systemic and environmental disease. The exposome (
Language	English
Publishing date	2022-07-12
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	80128-8
ISSN	1468-3288 ; 0017-5749
ISSN (online)	1468-3288
ISSN	0017-5749
DOI	10.1136/gutjnl-2022-327209
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