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Paper Citation Record · LEDGER

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data

As of 20 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2412.13234.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.13234 v2

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:33:59.477627Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

43 of 43 outbound references displayed

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  • verified fuzzy3
  • unresolved7
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 60199fde-7eb5-4916-ab85-6a8e7f26e92d · outbound

This paper cites The evidence base of US Food and Drug Administration approvals of novel cancer therapies from 2000 to 2020.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data The evidence base of US Food and Drug Administration approvals of novel cancer therapies from 2000 to 2020

Reference 1

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Observation 387e50aa-c4eb-49f5-b3aa-1620f1f3cd8c · outbound

This paper cites Cancer statistics, 2022.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Cancer statistics, 2022

Reference 2

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Observation 07610f60-c0da-422e-8a8a-4eb5979fd77a · outbound

This paper cites Influence of first-line chemotherapy regimen on survival outcomes of patients with advanced urothelial carcinoma who received second-line immune checkpoint inhibitors.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Influence of first-line chemotherapy regimen on survival outcomes of patients with advanced urothelial carcinoma who received second-line immune checkpoint inhibitors

Reference 3

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Observation cc970c51-6c89-4731-be7d-88706d770e83 · outbound

This paper cites Cost- Effectiveness of Immune Checkpoint Inhibition in BRAF Wild-Type Advanced Melanoma.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Cost- Effectiveness of Immune Checkpoint Inhibition in BRAF Wild-Type Advanced Melanoma

Reference 4

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Observation b3d47253-9e93-434e-8687-baae81da9147 · outbound

This paper cites Optimal sequencing strategies in the treatment of EGFR mutation– positive non–small cell lung cancer: Clinical benefits and cost-effectiveness.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Optimal sequencing strategies in the treatment of EGFR mutation– positive non–small cell lung cancer: Clinical benefits and cost-effectiveness

Reference 5

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Observation 0db5c772-c752-4c8b-8b75-6f3eda5531bf · outbound

This paper cites an unresolved cited work.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Unresolved cited work

Reference 6

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Observation aacf0430-1be9-448b-b309-c435a035ee1c · outbound

This paper cites Cost-effectiveness analysis of 1st through 3rd line sequential targeted therapy in HER2-positive metastatic breast cancer in the United States.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Cost-effectiveness analysis of 1st through 3rd line sequential targeted therapy in HER2-positive metastatic breast cancer in the United States

Reference 7

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Observation 5eedf5e0-b946-4a8c-9577-471b79240b34 · outbound

This paper cites A cost-effectiveness analysis of trastuzumab-containing treatment sequences for HER-2 positive metastatic breast cancer patients in Taiwan.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data A cost-effectiveness analysis of trastuzumab-containing treatment sequences for HER-2 positive metastatic breast cancer patients in Taiwan

Reference 8

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Observation f695d477-d7d6-4873-aae4-628c146bda97 · outbound

This paper cites Cost-Effectiveness Analysis of Different Sequences of the Use of Epidermal Growth Factor Receptor Inhibitors for Wild-Type KRAS Unresectable Metastatic Colorectal Cancer.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Cost-Effectiveness Analysis of Different Sequences of the Use of Epidermal Growth Factor Receptor Inhibitors for Wild-Type KRAS Unresectable Metastatic Colorectal Cancer

Reference 9

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Observation e3b31f10-a44d-48e9-aad3-d49a65c769ef · outbound

This paper cites State-Transition Modeling: A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force-3.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data State-Transition Modeling: A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force-3

Reference 10

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Unavailable: canonical work link unavailable.

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Observation 203b875c-6ae9-4cb4-bc7d-04cb83b76560 · outbound

This paper cites Microsimulation modeling for health decision sciences using R: a tutorial.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Microsimulation modeling for health decision sciences using R: a tutorial

Reference 11

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 3143f673-d453-42fa-8a57-ff9d36d24318 · outbound

This paper cites Cohort versus patient level simulation for the economic evaluation of single versus combination immuno-oncology therapies in metastatic melanoma.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Cohort versus patient level simulation for the economic evaluation of single versus combination immuno-oncology therapies in metastatic melanoma

Reference 12

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 4e17f87d-f310-4cd9-a36b-67d65cbe7df5 · outbound

This paper cites A Brief, Global History of Microsimulation Models in Health: Past Applications, Lessons Learned and Future Directions.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data A Brief, Global History of Microsimulation Models in Health: Past Applications, Lessons Learned and Future Directions

Reference 13

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 18220b1b-1190-4572-bc96-cfaf11cb5c3f · outbound

This paper cites Cost-Effectiveness Analysis for Therapy Sequence in Advanced Cancer: A Microsimulation Approach with Application to Metastatic Prostate Cancer.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Cost-Effectiveness Analysis for Therapy Sequence in Advanced Cancer: A Microsimulation Approach with Application to Metastatic Prostate Cancer

Reference 14

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation e78621de-1eda-4d54-8bf7-ff604c48608f · outbound

This paper cites Comparative effectiveness of cisplatin-based and carboplatin-based chemotherapy for treatment of advanced urothelial carcinoma.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Comparative effectiveness of cisplatin-based and carboplatin-based chemotherapy for treatment of advanced urothelial carcinoma

Reference 15

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation b7761051-0131-42ee-9b59-5670bc875165 · outbound

This paper cites Comparison of Population Characteristics in Real-World Clinical Oncology Databases in the US: Flatiron Health, SEER, and NPCR.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Comparison of Population Characteristics in Real-World Clinical Oncology Databases in the US: Flatiron Health, SEER, and NPCR

Reference 16

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Observation c10cb40d-011b-466c-b051-900e825cf062 · outbound

This paper cites Model-assisted cohort selection with bias analysis for generating large-scale cohorts from the EHR for oncology research.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Model-assisted cohort selection with bias analysis for generating large-scale cohorts from the EHR for oncology research

Reference 17

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Observation a519d23e-f62c-4db5-84b4-138e622d467e · outbound

This paper cites Tutorial in biostatistics: competing risks and multi- state models.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Tutorial in biostatistics: competing risks and multi- state models

Reference 18

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Observation d9470a70-f398-4bc7-b6ab-aedac077f1b4 · outbound

This paper cites mstate: An R Package for the Analysis of Competing Risks and Multi-State Models.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data mstate: An R Package for the Analysis of Competing Risks and Multi-State Models

Reference 19

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Observation 575a2915-f973-4a35-898d-a9124b2ce5a0 · outbound

This paper cites Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies

Reference 20

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Observation 86977154-1952-499b-b189-8763a6b435df · outbound

This paper cites Differences in target estimands between different propensity score- based weights.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Differences in target estimands between different propensity score- based weights

Reference 21

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Observation 0cee78d8-0da2-4f0f-8e07-2cbf8a23f59e · outbound

This paper cites Propensity score estimation: machine learning and classification methods as alternatives to logistic regression.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Propensity score estimation: machine learning and classification methods as alternatives to logistic regression

Reference 22

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Observation 989c4292-3e64-4897-9341-58eee842c95b · outbound

This paper cites A simulation procedure based on copulas to generate clustered multi-state survival data.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data A simulation procedure based on copulas to generate clustered multi-state survival data

Reference 23

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 49d9a322-baa9-4240-bb64-6968cdc04348 · outbound

This paper cites Modelling Dependence with Copulas in R | R-bloggers.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Modelling Dependence with Copulas in R | R-bloggers

Reference 24

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 818a159d-ced9-4a9f-a854-2656c6a8180e · outbound

This paper cites Markov Models and Cost Effectiveness Analysis: Applications in Medical Research.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Markov Models and Cost Effectiveness Analysis: Applications in Medical Research

Reference 25

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Observation c2bac506-5ac6-4c35-a0ef-e2beea7c5af8 · outbound

This paper cites Analysis of a Real-World Progression Variable and Related Endpoints for Patients with Five Different Cancer Types.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Analysis of a Real-World Progression Variable and Related Endpoints for Patients with Five Different Cancer Types

Reference 26

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 00f3eec9-1967-40a8-ab41-c8d66cd80418 · outbound

This paper cites Avelumab Maintenance Treatment After First-line Chemotherapy in Advanced Urothelial Carcinoma–A Cost-Effectiveness Analysis.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Avelumab Maintenance Treatment After First-line Chemotherapy in Advanced Urothelial Carcinoma–A Cost-Effectiveness Analysis

Reference 27

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation a89e3db4-8c83-46fb-999b-36be6497eb20 · outbound

This paper cites Quality of life in bladder cancer patients receiving medical oncological treatment; a systematic review of the literature.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Quality of life in bladder cancer patients receiving medical oncological treatment; a systematic review of the literature

Reference 28

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correction dated 2020-01-23. Source: crossref record 10.1186/s12955-019-1247-1->10.1186/s12955-018-1077-6:correction, observed 2026-07-11T03:01:30.67789+00:00. This notice travels one citation hop only.

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Observation 9870b5bf-3625-48f3-acc4-492e71f667b0 · outbound

This paper cites Cost-effectiveness of Pembrolizumab for Patients with Advanced, Unresectable, or Metastatic Urothelial Cancer Ineligible for Cisplatin- based Therapy.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Cost-effectiveness of Pembrolizumab for Patients with Advanced, Unresectable, or Metastatic Urothelial Cancer Ineligible for Cisplatin- based Therapy

Reference 29

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 64bb2b06-b346-4906-b14b-53eac204af90 · outbound

This paper cites Cost-effectiveness of Pembrolizumab in Second-line Advanced Bladder Cancer.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Cost-effectiveness of Pembrolizumab in Second-line Advanced Bladder Cancer

Reference 30

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 23c52861-32f1-43f1-8643-aed04ce4bce0 · outbound

This paper cites an unresolved cited work.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Unresolved cited work

Reference 31

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 20c0800a-de9c-4c17-8d08-278128b3d900 · outbound

This paper cites Pembrolizumab as Second-Line Therapy for Advanced Urothelial Carcinoma.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Pembrolizumab as Second-Line Therapy for Advanced Urothelial Carcinoma

Reference 32

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 4d06331d-1ce0-4451-b36f-e5125b6e1527 · outbound

This paper cites Accessed November 7, 2024.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Accessed November 7, 2024

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:34:00.528467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation f10c88c0-8ef5-4ba6-8eda-539225711e9f · outbound

This paper cites an unresolved cited work.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Unresolved cited work

Reference 34

Resolution
verified exact
doi, observed 2026-08-11T13:33:59.564784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 28af06d2-bce8-40f3-9f58-773669d41142 · outbound

This paper cites The cost effectiveness of pembrolizumab versus chemotherapy or atezolizumab as second-line therapy for advanced urothelial carcinoma in the United States.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data The cost effectiveness of pembrolizumab versus chemotherapy or atezolizumab as second-line therapy for advanced urothelial carcinoma in the United States

Reference 35

Resolution
verified exact
raw_fallback, observed 2026-08-11T13:34:00.095564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation f6f91b4e-685c-451c-aab4-8253aa096294 · outbound

This paper cites Using Electronic Health Records to Identify Adverse Drug Events in Ambulatory Care: A Systematic Review.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Using Electronic Health Records to Identify Adverse Drug Events in Ambulatory Care: A Systematic Review

Reference 36

Resolution
verified exact
doi, observed 2026-08-11T13:33:59.553810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T13:33:59.455032Z digest=sha256:3a8f9cc511cb88d9ea2df6191fd29d02f649f852c83ac41155d6a9224c70f95e

Observation 5e77ab4a-3779-4eae-a4fa-546c336d941e · outbound

This paper cites Automated Identification of Patients With Immune-Related Adverse Events From Clinical Notes Using Word Embedding and Machine Learning.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Automated Identification of Patients With Immune-Related Adverse Events From Clinical Notes Using Word Embedding and Machine Learning

Reference 37

Resolution
verified exact
doi, observed 2026-08-11T13:33:59.543195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T13:33:59.458769Z digest=sha256:8ad95303bf931c6ac979a0419a42a0dc73738d00934438c9695248bd9990a3fa

Observation a8977a12-3360-4089-b13e-09076ae137e8 · outbound

This paper cites Dealing with Time in Health Economic Evaluation: Methodological Issues and Recommendations for Practice.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Dealing with Time in Health Economic Evaluation: Methodological Issues and Recommendations for Practice

Reference 38

Resolution
verified exact
doi, observed 2026-08-11T13:33:59.531819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T13:33:59.462353Z digest=sha256:5b777688c19393acd1a2112d8a1cd6fd3885093643ec1058e318923998dd093b

Observation f6a0b32b-d793-4375-8746-9381d6044e59 · outbound

This paper cites A Proportional Hazards Model for the Subdistribution of a Competing Risk.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data A Proportional Hazards Model for the Subdistribution of a Competing Risk

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-11T13:33:59.466677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:33:59.466677Z digest=sha256:8295049bac9834cff44b6cb5eecd502fad0acb3b87ac3c39de191446c18fbadf

Observation b1fb377f-4aff-4d96-98cb-03003529b157 · outbound

This paper cites Fine-Gray subdistribution hazard models to simultaneously estimate the absolute risk of different event types: Cumulative total failure probability may exceed 1.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Fine-Gray subdistribution hazard models to simultaneously estimate the absolute risk of different event types: Cumulative total failure probability may exceed 1

Reference 40

Resolution
verified exact
doi, observed 2026-08-11T13:33:59.521394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T13:33:59.470415Z digest=sha256:6e826e6c1c3edf6e1d0b4d32f27ee580e6cfa9e12819c8d4389e7ef56a7e3177

Observation 4d2729f1-0b8a-4b4d-b3e0-93d426e51c8e · outbound

This paper cites Bayesian, and Non-Bayesian, Cause-Specific Competing-Risk Analysis for Parametric and Nonparametric Survival Functions: The R Package CFC.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Bayesian, and Non-Bayesian, Cause-Specific Competing-Risk Analysis for Parametric and Nonparametric Survival Functions: The R Package CFC

Reference 41

Resolution
verified exact
doi, observed 2026-08-11T13:33:59.509216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T13:33:59.473882Z digest=sha256:1442eedb439f321b4639912156b0a779fbcf9519e93cd8eca0b641516762987d

Observation 2956726b-8c5b-4b52-b08f-5a87a566d880 · outbound

This paper cites Performance of a Machine Learning Algorithm Using Electronic Health Record Data to Identify and Estimate Survival in a Longitudinal Cohort of Patients With Lung Cancer.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Performance of a Machine Learning Algorithm Using Electronic Health Record Data to Identify and Estimate Survival in a Longitudinal Cohort of Patients With Lung Cancer

Reference 42

Resolution
verified exact
raw_fallback, observed 2026-08-11T13:33:59.905115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T13:33:59.477627Z digest=sha256:8588eea7fe6f3c64f4d922ca86c992ff1bf5720d76f0b541b00e494af637ca0a

Observation e4d8d1e0-65aa-4e40-84aa-86c92a4709cb · outbound

This paper cites an unresolved cited work.

Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data Unresolved cited work

Reference 1026

Resolution
verified exact
doi, observed 2026-08-11T13:33:59.575860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T13:33:59.438631Z digest=sha256:259602ace3c7e645e39425f7106c3b125f703a9da28e8d1728462565d129616b

Pith citing papers

No inbound Pith citation observations are available.