Elliot A. Asare

Improving the quality of cancer staging.

In this era of multidisciplinary management of the patient with cancer, there is a critical need for accurate information related to the patient, tumor characteristics, and treatment received or planned to facilitate the quality of care delivered. Staging has been a core component of cancer care for decades, and the rapidly evolving pace of oncology calls for measures to improve the quality of cancer staging. The Institute of Medicine report on improving the quality of cancer care noted that “in order to continue to advance the high-quality cancer care delivery system, measurement and assessment of progress in improving the delivery of cancer care, public reporting of information gathered, and development of innovative strategies to facilitate performance improvement will be needed.” This charge from the Institute of Medicine calls for adherence to existing quality indicators (QIs) or measures (QMs), practice guidelines, and the creation of new QIs or QMs when none exist. The American Joint Committee on Cancer (AJCC) is engaged in several efforts to improve the quality of cancer staging. QIs are well-defined, quantifiable targets that allow for the assessment of structure, process, and outcome with regard to care. QIs must be measurable, actionable, and based on evidence. In addition, QIs should serve as benchmarks for the comparison of different metrics associated with care across many institutions. Among several important QIs and QMs for the care of the patient with cancer, accurate and complete documentation of cancer stage has critical implications for the patient, clinician, and public health scientists. Clinicians involved in the care of the patient with cancer, cancer registries, and other users of staging data look to the AJCC to formulate and revise the rules for cancer staging in the United States. Established in 1959, the AJCC has been collaborating with the Union for International Cancer Control since 1982 to provide a unified anatomic staging system for cancer worldwide. Updates to the staging system are performed periodically by convening the best expertise in the field and using the highest available level of evidence. Previous editions of the AJCC staging system have included nonanatomic prognostic factors within the TNM framework for some disease sites. Expansion of staging to include widely accepted pertinent prognostic factors for many other disease sites is also currently under consideration in the ongoing efforts to develop the 8th edition of the AJCC staging system. Accurate staging allows the clinician to offer patients treatment recommendations based on practice guidelines and to discuss prognosis. Cancer stage also serves as an important inclusion, exclusion, and/or stratification criterion for clinical trials. In addition to other variables, data elements with which to derive disease stage are abstracted into the National Cancer Data Base (NCDB), the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) database, and the Center for Disease Control’s (CDC’s) National Program of Cancer Registries (NPCR). These data elements allow for research into disease outcomes and trends over time based on stage of disease when necessary and are informative in the formulation of guidelines, targeted population cancer control efforts, and allocation of resources. Importantly, staging facilitates national and international collaborative cancer research efforts, and allows clinicians from different cultural and language backgrounds to communicate and share data regarding cancer. This is especially important as the global burden of cancer cases continues to rise, especially in lowincome and middle-income countries. Despite the fundamental role of cancer staging, timely and accurate stage assignment with appropriate documentation can be difficult to achieve in practice. First, ambiguities in portions of the AJCC staging manual leave interpretation of staging rules to the clinician or registrar, either of whom may be incorrect. Critical to improving quality staging data are cancer registrars, who are personnel with specialized training to abstract pertinent information with regard to the history, diagnosis, treatment, and

A novel staging system for adrenocortical carcinoma better predicts survival in patients with stage I/II disease

BACKGROUND Current American Joint Committee on Cancer/International Union against Cancer (AJCC/UICC) and European Network for the Study of Adrenal Tumors staging for adrenocortical carcinoma (ACC) have not shown a survival difference between patients with stage I/II disease. This study evaluates current staging systems for survival prediction using a larger cohort and assesses whether incorporating age into ACC staging improves survival predictions. METHODS Patients in the National Cancer Data Base (1985-2006) with a diagnosis of ACC were identified and staged using a novel TNM-A staging system: Stage I (T1/T2N0M0, age ≤ 55), stage II (T1/T2N0M0, age >55), stage III (T1/T2N1M0 or T3/T4N0-N1M0, any age), or stage IV (any T any NM1, any age). Differences in overall survival (OS) by stage were compared using a Cox proportional hazards model. RESULTS Staging was derived for 1,579 of 3,262 patients. Median age was 54 years; mean tumor size was 11.6 cm. Using current staging, differences in 5-year OS was observed only between patients with stages II/III and III/IV ACC. With TNM-A staging, differences in 5-year OS between all stages was significant (I/II [P < .003], II/III [P < .0001], III/IV [P < .0001]). CONCLUSION A staging system that incorporates patient age better predicts 5-year OS among patients with stages I/II ACC. Consideration should be given to including age in staging for ACC, because it may better inform providers about treatment and prognosis.

Risk prediction tools in surgical oncology

Healthcare has increasingly focused on patient engagement and shared decision‐making. Decision aids can promote engagement and shared decision making by providing patients and their providers with care options and outcomes. This article discusses decision aids for surgical oncology patients. Topics include: short‐term risk prediction following surgery, long‐term risk prediction of survival and recurrence, the combination of short‐ and long‐term risk prediction to help guide treatment choice, and decision aid usability, transparency, and accessibility. J. Surg. Oncol. 2014 110:500–508.

Neoadjuvant treatment sequencing adds value to the care of patients with operable pancreatic cancer.

Treatment sequencing for resectable pancreatic cancer remains controversial and there is lack of level one evidence comparing neoadjuvant versus adjuvant strategies. However, a comparison of the cost‐effectiveness analysis of the treatment strategies may help to better define the healthcare value of each approach. This review will highlight the rationale for multimodality therapy in the treatment of pancreatic cancer, discuss the advantages and disadvantages of adjuvant therapy, and conceptualize the cost‐effectiveness of a neoadjuvant approach with regard to healthcare value. J. Surg. Oncol. 2016;114:291–295.

Cervical Lymph Nodes and Unknown Primary Tumors of the Head and Neck

Risk Assessment Models The AJCC recently established guidelines that will be used to evaluate published statistical prediction models for the purpose of granting endorsement for clinical use. Although this is a monumental step toward the goal of precision medicine, this work was published only very recently. Therefore, the existing models that have been published or may be in clinical use have not yet been evaluated for this cancer site by the Precision Medicine Core of the AJCC. In the future, the statistical prediction models for this cancer site will be evaluated, and those that meet all AJCC criteria will be endorsed.

Soft Tissue Sarcoma of the Head and Neck

Risk Assessment Models The AJCC recently established guidelines that will be used to evaluate published statistical prediction models for the purpose of granting endorsement for clinical use. Although this is a monumental step toward the goal of precision medicine, this work was published only very recently. Therefore, the existing models that have been published or may be in clinical use have not yet been evaluated for this cancer site by the Precision Medicine Core of the AJCC. In the future, the statistical prediction models for this cancer site will be evaluated, and those that meet all AJCC criteria will be endorsed.

Neuroendocrine Tumors of the Jejunum and Ileum

AJCC Cancer Staging Manual, 8th Edition Copyright 2016 American Joint Committee on Cancer. All rights reserved. Version 1 | Page 1 of 2 Authors Eugene A. Woltering, Emily K. Bergsland, David T. Beyer, Thomas M. O’Dorisio, Guido Rindi, David S. Klimstra, Laura H. Tang, Diane Reidy-Lagunes, Jonathan R. Strosberg, Edward M. Wolin, Aaron I. Vinik, Eric K. Nakakura, Elliot A. Asare, David L. Bushnell, Richard L. Schilsky, Yi-Zarn Wang, Michelle K. Kim, Eric H. Liu, Robert T. Jensen, Rebecca K.S. Wong, John K. Ramage, Kathy Mallin, Rodney F. Pommier

Comparative Effectiveness in Thyroid Cancer: Key Questions and How to Answer Them

Controversies in treatment of thyroid cancer remain despite numerous published studies. Robust comparative effectiveness studies examining: (1) the role of prophylactic central compartment neck dissection (pCCND) in patients with papillary thyroid cancer (PTC); (2) the use of post-operative radioactive iodine (RAI) ablation therapy following total thyroidectomy; (3) use of low versus high doses of I-131 in RAI therapy; (4) thyroid hormone withdrawal (THW) versus recombinant thyroid stimulating hormone (rhTSH) prior to RAI; and (5) the role of routine measurement of serum calcitonin levels are needed to help strengthen existing treatment recommendations. Reasons for the controversies and suggestions for quality comparative effectiveness studies are discussed.

Soft Tissue Sarcoma of the Trunk and Extremities

Risk Assessment Models The AJCC has recently established guidelines that will be used to evaluate published statistical prediction models for the purpose of granting endorsement for clinical use. Although this is a monumental step forward towards the goal of precision medicine, this work was only very recently published. For this reason, the existing models that have been published or may be in clinical use have not yet been evaluated for this cancer site by the Precision Medicine core of the AJCC. In the future, the statistical prediction models for this cancer site will be evaluated, and those that meet all AJCC criteria will be endorsed.

Unusual Pancreatic Tumors

Abstract Pancreatic ductal adenocarcinoma and cystic neoplasms of the pancreas account for the majority of all pancreatic neoplasms. However, there is a subset of rare and unusual conditions of the pancreas that have been increasingly identified over the past two decades, in part by increased use of computed tomography. These conditions can often be challenging to clinicians because the presentation and diagnostic findings can often mimic pancreatic ductal adenocarcinoma. This chapter will focus on these less appreciated lesions and will discuss the optimal diagnostic and therapeutic approaches to their management.