Wait times from diagnosis to treatment in cancer

The effect of surgical timing in nonmetastatic melanoma

BACKGROUND AND OBJECTIVES

There is no consensus guidelines on the best timing to perform Sentinel lymph node biopsy (SLNB) in high-risk melanoma patients. We aimed to understand the impact of surgical timing on nodal upstaging in patients with cutaneous melanoma.

METHODS

We queried the National Cancer Database from 2004 to 2018 for patients with T2-T4, N0, M0 melanomas, who underwent melanoma excision and nodal surgery. We included patients who underwent surgery within 2-19 weeks postdiagnosis. We aimed to determine the association of surgical delay (weeks) with nodal positivity.

RESULTS

A total of 53 355 patients were included, of whom 20.9% had positive lymph nodes. Patients underwent surgery at a median of 5 (4-7) weeks after diagnosis. The rate of positive nodes increased with increased weeks to surgery (line of best-fit slope = 0.38). Multivariable regression analysis identified an association between time to surgery and nodal positivity (2.4% increased risk per week, p < 0.05). Our analysis showed significantly increased likelihood of nodal positivity beginning 9 weeks after diagnosis (odds ratio [OR] = 1.3, p < 0.05). Furthermore, patients with T2-3 tumors had a significant increase in nodal positivity with increased time to surgery (OR = 1.03 per week, p < 0.001). However, no significant trend in nodal positivity was identified for patients with T4 melanomas (OR = 1.01 per week, p = 0.596).

CONCLUSION

Surgery within 9 weeks of melanoma diagnosis was not associated with increased likelihood of nodal positivity. These data can guide clinical conversations regarding the importance of surgical timing for melanoma.

Identification of an oncological clinical pathway through questionnaires to health professionals

BACKGROUND

Clinical Pathways in Oncology can benefit patients using organized interventions to standardize and increase care efficiency. Healthcare systems should have tools to identify their oncological clinical pathways for a better institutional organization to reduce mortality rates and contain costs without compromising quality. Our objective is to determine the regional Oncology Clinical Pathway from a first basic hypothesis using questionnaires directed to healthcare professionals considered key deciders within the Pathway.

METHODS

Study design consisted of data analysis of two structured region-wide questionnaires; built using available literature on Oncology Clinical Pathways, in a Portuguese Healthcare context and pre-tested in a focus group of key deciders (Physicians and nurses with management functions) from which a design was created. Queries analyzed the patients: tumor staging at service arrival; time intervals on tumor suspicion/diagnosis confirmation and diagnosis/first treatment; referral pathway; diagnostic networks and patient Follow-up. One questionnaire was sent to key deciders directly involved with Oncology patients at a Regional Hospital. 15 physicians and 18 nurses of this sample answered the questionnaire (approx. response rate = 67%). Another questionnaire sent to healthcare professionals in Primary Healthcare Centers yielded response rate 19.2%, N = 29 physicians and 46 nurses. Finally, we performed a descriptive analysis and a Cronbach Alpha reliability analysis.

RESULTS

Our findings reveal: different appreciations of tumor staging at arrival in Primary Healthcare Centers and Regional Hospitals (the latter receiving more metastatic cases); approximately 4 weeks between tumor suspicion-diagnostic and divided opinions regarding diagnostic-treatment time intervals. Primary Healthcare Centers depend on private laboratories for diagnostics confirmation, while the Hospitals resolve this locally. Referral pathways indicate almost half of the patients being sent from primary healthcare centers to National Reference Hospitals instead of a Regional Hospital. Patient follow-up is developed throughout the institutions, however, is more established at Regional Hospitals. As patients advance through the Oncology Clinical Pathway and toward treatment stages the number of healthcare professionals involved reduce.

CONCLUSION

Our questionnaires enable us to understand the real pathway between the different institutions involved and the main entry points of the patients into the Oncology Clinical Pathway.

Predicting Patient-Specific Tumor Dynamics: How Many Measurements Are Necessary?

Acquiring sufficient data is imperative to accurately predict tumor growth dynamics and effectively treat patients. The aim of this study was to investigate the number of volume measurements necessary to predict breast tumor growth dynamics using the logistic growth model. The model was calibrated to tumor volume data from 18 untreated breast cancer patients using a varying number of measurements interpolated at clinically relevant timepoints with different levels of noise (0-20%). Error-to-model parameters and the data were compared to determine the sufficient number of measurements needed to accurately determine growth dynamics. We found that without noise, three tumor volume measurements are necessary and sufficient to estimate patient-specific model parameters. More measurements were required as the level of noise increased. Estimating the tumor growth dynamics was shown to depend on the tumor growth rate, clinical noise level, and acceptable error of the to-be-determined parameters. Understanding the relationship between these factors provides a metric by which clinicians can determine when sufficient data have been collected to confidently predict patient-specific tumor growth dynamics and recommend appropriate treatment options.

The wait time to primary surgery in endometrial cancer - impact on survival and predictive factors: a population-based SweGCG study

BACKGROUND

Poor survival rates in different cancer types are sometimes blamed on diagnostic and treatment delays, and it has been suggested that such delays might be related to sociodemographic factors such as education and ethnicity. We examined associations of the wait time from diagnosis to surgery and survival in endometrial cancer (EC) and explored patient and tumour factors influencing the wait time.

MATERIAL AND METHODS

In this historical population-based cohort study, The Swedish Quality Registry for Gynaecologic Cancer (SQRGC) was used to identify EC patients who underwent primary surgery between 2010 and 2018. Factors associated with a wait time > 32 d were analysed with logistic regression. The 32-d time point was defined in accordance with the Swedish Standardisation Cancer Care programme. Adjusted Poisson regression analyses were used to analyse excess mortality rate ratio (EMRR).

RESULTS

Out of 7366 women, 5535 waited > 32 d for surgery and 1098 > 70 d. The overall median wait time was 44 d. The factors most strongly associated with a wait time > 32 d were surgery at a university hospital (adjusted odds ratio [OR] 1.34, 95% confidence interval [CI] 1.08-1.66) followed by country of birth (OR 1.31, 95% CI 1.10-1.55) and year of diagnosis. There were no associations between wait time and histology or age. A wait time < 15 d was associated with higher mortality (adjusted EMRR 2.29,95% CI 1.36-3.84) whereas no negative survival impact was seen with a wait time of 70 d. Age, tumour stage, histology and risk group were highly associated with survival, whereas education, country of origin and hospital level did not have any impact on survival.

CONCLUSIONS

Surgery within the first two weeks after EC diagnosis was associated with worsened survival. A prolonged wait time did not seem to have any significant adverse effect on prognosis.HighlightsSurgery within the first two weeks after diagnosis of endometrial cancer (EC) was associated with poorer survival.A prolonged wait time to surgery did not worsen prognosis.Delay in time to surgery was associated with sociodemographic factors.

Rural Standards and the Quality Equation

The article describes the barriers rural surgeons face when attempting to measure, analyze, and benchmark the quality and value of the care they provide for their patients. Examples of suboptimal care are presented as well as special geographic and resource-related circumstances for many of these disparities of care. The article includes in-depth descriptions of the American College of Surgeons (ACS) Optimal Resources for Surgical Quality and Safety Program and the ACS Rural Hospital Surgical Verification and Quality Improvement Program. The article concludes by discussing several documented clinical, economic, and social advantages of keeping surgical care local.

Association between complementary and alternative medicine use and prolonged time to conventional treatment among Thai cancer patients in a tertiary-care hospital

Objectives

The purpose of this study is to investigate the patterns of complementary and alternative medicine use and its association with time to conventional treatment.

Design

A cross-sectional study design was designed.

Setting and participants

The study was performed at the Chonburi Cancer Hospital, with chart reviews and interviews performed for 426 patients with various cancers between May and December 2018.

Results

The results indicated that 192 of the 426 patients (45.1%) reported using complementary and alternative medicines; herbal products were the most common type. Approximately 34.3% of these medicines involved unlabeled herbal products with unidentifiable components. The rates of complementary and alternative medicine use were significantly elevated for men and patients with stage IV cancer. The multivariable linear regression analysis of the relationship between factors and the time until conventional treatment was received revealed that the regression coefficient of the use of complementary and alternative medicine was 56.3 (95% confidence interval [27.9-84.6]). This coefficient reflected an additional 56.3 days of time until conventional treatment, relative to patients who did not use complementary and alternative medicine.

Conclusions

The present study revealed that complementary and alternative medicine use was fairly common among Thai patients with cancer and was associated with a prolonged time to receiving conventional treatment.