Introduction
Innovative interventions in cancer treatment may
improve the survival rate of patients; however, such improvements
may bear a substantial economic cost (1). Thus far, the evaluation of cancer
therapeutic efficacy is only dependent on medical indicators
(2-5).
In some cases, the high-cost treatment may reach the same goal as
the low-cost regimen. The assessment of treatment efficacy is
mainly based on the opinions of the medical doctors. However, there
are numerous subjective and objective factors affecting the
judgement of experts; thus, the current assessment criteria are not
comprehensive and objective, and are perhaps against the principles
of fairness and impartiality. Therefore, it is necessary to
comprehensively and objectively assess the quality of cancer care
as the concept of value must be incorporated into cancer care
(6).
The present study designed a quantitative
cost-effectiveness index (QCEI) of cancer treatments, which may be
a more objective and impartial indicator to assess the
effectiveness of available options for malignancies.
Patients and methods
Hospitalization expense index
(HEI)
Though hospitalization expense is frequently
discussed by various researchers (7,8), there
is no a specific index to assess it. The HEI, a novel economic
index which can be used to evaluate the efficacy of malignancy
treatment, was calculated as follows: HEI=individual expense in the
first year/average expense of all patients in the first year
(hospital expense). As regards the total hospitalization expense
index (THEI) of cooperative hospitals, it can be calculated using
following formula: THEI=individual hospital HEI in the first
year/average hospital HEI in the first year. The larger value of
the index indicates a better economic value with a mean value of
1.0.
Efficacy evaluation index (EEI)
The EEI is an index to evaluate the curative effects
on malignancies (9,10) and was calculated using the following
formula: EEI=(individual survival time within three or five
year)/(average survival time of all patients with the same disease
from a center or hospital within three year or five year). As such,
the EEI for cooperative hospitals was calculated as follows:
EEI=(average survival time of patients from a hospital within three
year or five year)/(mean survival time of hospitals within three
year or five year). A higher EEI demonstrates a better curative
effect with an average value of 1.0. This is the relative ratio,
which should also include the number of cases and consider the
ratio of the survival to the number of cases. The following example
is 4.265:25 of EEI (the international reference value is 3.845:
large sample).
EEI is crucial for assessing efficacy when
reflecting the basis of medical care. Normally, the ratio of HEI
and EEI will be 1/2. For example, in acute myeloid leukemia (AML),
when calculating the HEI, refractory secondary AML, mixed AML and
tractable subtypes such as M3 AML and myeloid leukemia associated
with Down syndrome should be excluded. In cases of <20 patients,
the HEI and EEI can be calculated regardless of the risk difference
of disease. HEI and EEI are relative evaluation indexes (absolute
indexes should include other factors).
Risk distribution
AML can be simplified into the favorable,
intermediate and adverse-risk categories (11,12). The
favorable-risk group requires the following conditions: M2 AML
patients (age, ≥10 years) hardly achieving remission after two
courses of therapy, with a white blood cell count
≥100x109/l. The intermediate risk group includes
patients achieving remission after two courses of induction
therapy. The adverse-risk group includes those achieving remission
after one course of induction therapy.
Innovation, improvement and
inheritance
Innovation herein refers to the development of a new
method or regimen. It tends to significantly improve the efficacy
of clinical treatment in clinical practice (13). Improvement refers to making changes
to existing treatments to improve clinical diagnosis and patient
prognosis. Inheritance refers to the application of currently
advanced therapeutics and chemotherapeutics to achieve
international standards for the treatment.
Retrospective and prospective
studies
A prospective study usually contains double-blind
and placebo-controlled trial with complete record data from no
<20 patients who receive the same regimen. Each subtype of AML
varies in risk, and high-risk and ultra-high-risk categories are
the main targets of researches. In a prospective study on AML, the
cases of curable M3 and myeloid leukemia associated with Down
syndrome, as well as refractory secondary leukemia (14) including chronic granulocytic leukemia
and Langerhans cell histiocytosis (15), juvenile myelomonocytic leukemia
(16), and hybrid AML should be
excluded. .
A retrospective study, also known as a case control
study, looks backwards and examines potential factors in relation
to an outcome. A prospective study looks for outcomes and usually
involves taking a cohort of subjects and examining them over a long
period of time (17,18).
Assessment of innovation under
specific conditions
Some innovative studies are published as
retrospective analyses due to various reasons (19). Their findings with statistically
reliable data are still considered as innovative or beneficial. If
no study has ever reported the finding at home, the study belongs
to domestic innovation. If no study has reported the finding
worldwide, the outcome should be considered as an international
innovation or improvement. During calculation, some patients with
recurrence and treatment-related mortality should also be included
in the formula.
Data collection
The present examined the HEI and EEI of 16 cases of
childhood AML who received high-dose chemotherapy (HDCT) with
cytarabine (Table I) from January,
2010 to December, 2020 through the Hospital Information Systems of
the First Affiliated Hospital of Guangzhou Medical University. All
cases were diagnosed as AML according to the 2008 WHO
Classification of Tumors of Hematopoietic and Lymphoid Tissues
(20). Of note, some cases were
included in a trial of HDCT by Wu et al (21), with an 80% 5-year survival rate.
Prior to data collection, written informed consents were obtained
from the legal guardians of each participant and approval was
obtained from the Ethics Committee of the First Affiliated Hospital
of Guangzhou Medical University (Guangzhou, China).
 | Table IGeneral information of the 16 patients
with pediatric acute myeloid leukemia. |
Table I
General information of the 16 patients
with pediatric acute myeloid leukemia.
| Patient no. | Age (years) | Typing | Risk | Total cost ($) | First year expense
($) | Prognosis | Survival time
(days) |
|---|
| 1 | 7 | M2a | Intermediate | 51,600 | 38,360 | Survival | 3,260 |
| 2 | 8 | M2a | Data loss | 35,000 | 25,710 | Survival | 3,155 |
| 3 | 12 | M4a | Adverse | 39,500 | 27,930 | Survival | 2,868 |
| 4 | 7 | M1 | Intermediate | 43,500 | 31,090 | Survival | 2,591 |
| 5 | 8 | M2/M3 | Adverse | 35,100 | 35,070 | Relapse | 392 |
| 6 | 2 | M5 | Intermediate | 32,000 | 31,970 | Relapse | 311 |
| 7 | 7 | M4a | Intermediate | 51,600 | 44,900 | Death | 511 |
| 8 | 5 | M4a | Intermediate | 139,900 | 88,300 | Survival | 798 |
| 9 | 4 | M2a | Intermediate | 60,500 | 31,050 | Survival | 746 |
| 10 | 4 | M6 | Favorable | 63,700 | 40,270 | Survival | 634 |
| 11 | 3 | M6 | Favorable | 82,700 | 58,300 | Survival | 543 |
| 12 | 4 | M2a | Intermediate | 77,400 | 55,760 | In treatment | 395 |
| 13 | 1 | M5 | Intermediate | 64,700 | 40,580 | In treatment | 414 |
| 14 | 11 | M0 | Intermediate | 98,600 | 83,530 | In treatment | 246 |
| 15 | 11 | M4a | Adverse | 61,700 | 61,650 | In treatment | 253 |
| 16 | 11 | M4a | Adverse | 74,900 | 67,050 | In treatment | 135 |
| Mean value | | | | 63,275 | 47,595 | | 1,078.25 |
Results
Complete formula of the QCEI
Based on the sum of HEI (1.2 point) and EEI (1
point), the measurement of the QCEI of cancer treatments takes the
following factors into consideration: i) Follow-up duration of ≥18
months +0.02, ≥3 years +0.05, ≥5 years +0.08; ii) ≥20 cases +0.03;
5-year event-free survival (EFS) >1% +0.03 (75% of international
level); 3-year EFS>1% +0.05; iii) prospective innovative study,
+1.3; retrospective innovative study, +1.2; iv) prospective study
with improvement in treatment +0.8, retrospective study with
improvement +0.6; v) prospective study using an inherited regimen
+0.4, retrospective study using an inherited regimen +0.2; vi)
recurrence: ≥1/10-0.01, ≥2/10-0.02; vii) mortality rate:
≥1/10-0.015. The complete formula is demonstrated in Table II.
| Table IIFormula used for the indexes. |
Table II
Formula used for the indexes.
| Index | Denominator | Numerator | Formula |
|---|
| Hospitalization
expense index (HEI) | Individual
hospitalization expense in the first year (individual expense) | Average expense of
all patients in the first year (hospital expense) | HEI=individual
expense/hospital expense |
| Efficacy evaluation
index (EEI) | Individual survival
time within three or five years | Average survival
time of all patients | EEI=individual
survival time/Average survival time |
| Quantitative
cost-effectiveness index (QCEI) | | | QCEI=HEI + EEI +
score (follow-up) + (degree of innovation) + score (case) + score
(EFS)-score (mortality and recurrence rate) |
The retrospective analysis developed a new treatment
for AML with a >5-year follow-up and a low rate of recurrence
(12.5%) and mortality (<10%); thus, it obtained a high score of
4.265. Based on the factors in the study, the overall score of all
types of studies is demonstrated as follows: i) The total score of
a prospective innovative study, 4.345 points; ii) a retrospective
innovative study, 4.245; iii) a prospective study making a
contribution to treatment, 3.845; iv) a retrospective study
promoting developments in treatment, 3.645; v) a prospective study
using an advanced approach, 3.215; vi) a retrospective study using
a previous approach with a score of 2.2 is also an advanced study,
as the average QCEI of studies worldwide is 2.0. The above scores,
compared in different ranges, are the highest local level.
Discussion
The efficacy of the HDCT approach has reached an
international leading level. Our study pioneered treatment with
chemotherapy alone. As an innovative retrospective study, its score
of quantitative cost-effectiveness index was 4.265. The prospective
innovative study on childhood AML at the front line has achieved a
QCEI score of 3.845.
Of the 16 cases included in the example, there were
4 cases of adverse-risk AML, 9 cases of intermediate-risk AML, and
2 cases of favorable-risk AML (risk ratio,
(adverse:intermediate:favorable risk=4:9:2). Among the adverse-risk
AML cases, 1 case of M2a AML was generally considered more
manageable. The intermediate risk groups included 2 cases of M4a,
and 2 cases of M2. The favorable risk group consisted of 2 cases of
M6. Therefore, the difference in risk degree among three categories
of AML was not noteworthy.
With the measurement of EEI and HEI, the QCEI of
cancer treatment may effectively reflect the value of therapies and
thereby warrants further investigation and application. However,
since this is the first version of the QCEI of cancer treatment,
further studies are required. The index potently provides an
available method for the assessment of treatments for cancer, which
may also contribute to the development of health and medical
publishing. Cost-effectiveness analysis (CEA) is used to support
health sector decisions about the allocation of limited resources
and contribute to policy management and inequality aversion
(22). A recent study performed CEA
to assess cost-effectiveness by comparing diagnostic test results,
coronary revascularization, incident major adverse cardiovascular
event, and costs during 60 days and 2 years (23). Compared with this approach and other
CEAs, the QCEI in the present study clearly indicates the
effectiveness when tailoring the benefits of treatment and focuses
on cancer patients. In this case, QCEI may directly recommend
suitable and economical treatment options to patients and policy
makers.
AML is a relatively rare, yet costly type of cancer,
currently characterized by high-cost intensive treatments that
often require hospitalization. Currently, in the USA, the total
mean episode costs are highest in relapsed/refractory (R/R)
episodes ($439,104), followed by hematopoietic stem cell
transplantation ($329,621) and high-intensity chemotherapy
($198,657) (24,25). Such an economic burden is too heavy
for numerous families, particularly those in developing countries
(26). The comprehensive evaluation
of the treatment efficacy and expense is crucial to therapy
treatment. Only when the treatment efficacy is ensured and the
treatment costs are reduced, can more AML patients be able to
receive first-line treatments (27).
Moreover, as cancer survival rates rise, so does the cost of
life-saving treatments (28). Over
the past two decades, health spending on cancer has increased more
rapidly than the increase in cancer incidence (29). There is no single strategy that would
be optimal for all patients with a given disease. It is essential
to find a strategy to assess the cost and effectiveness of
treatments against cancer. In recent years, with regard to cancer,
precision medicine is often advocated, combined with gene-targeted
therapy and immune-targeted approaches (30). In this manner, health care providers
can offer and plan specific care for their patients, based on
financial condition, behaviors, habits and genes.
In conclusion, the QCEI of cancer treatment
developed in the present study might help policy makers,
physicians, and the society to share the decision making for cancer
management, contributing to the development of precision medicine
as well.
Acknowledgements
The authors would like to thank Mr. Linwei Ma
(School of Foreign Languages, Southern Medical University,
Guangzhou, China) for translating the manuscript, processing the
table and for assisting with manuscript revision.
Funding
Funding: No funding was received.
Availability of data and material
The datasets generated and/or analyzed during the
current study are not publicly available due to the privacy of
patients, but are available from the corresponding author on
reasonable request.
Authors' contributions
ZW proposed and created the quantitative
cost-effectiveness index of cancer treatment; wrote the draft of
the manuscript, and calculated the data of each patient. YY
recorded the patient data regarding pediatric acute myeloid
leukemia and calculated the cost of treatment for each patient
together with ZW. DC supervised the study for years and applied for
ethics approval to the hospital, and was also involved in data
collection. All authors have read and approved the final
manuscript. DC and YY confirm the authenticity of all the raw
data.
Ethics approval and consent to
participate
Prior to data collection, written informed consents
were obtained from the legal guardians of each participant and
approval was obtained from the Ethics Committee of the First
Affiliated Hospital of Guangzhou Medical University (Guangzhou,
China).
Patient consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing
interests.
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